>> (upbeat music) >> Okay, we just covered some of the critical aspects from Infinidat recent announcement and the importance of cyber resilience and fast recovery. Eric Hertzog is back and joining us is Stan Wysocki, who's president of Mark III Systems. Stan, welcome to the Cube, good to see you. >> Thank you, pleasure to be here. >> Tell us about Mark III Systems. You specialize in IT infrastructure and artificial intelligence. It says in your website. I'd love to hear more about your business. >> Yeah, yeah, definitely. You know, I think we're a little bit unique in our industry, right? There've been business partners resellers around for, we've been around for 26 years. And in 26 years, we've supported some of largest enterprise customers in the Southeast, with server storage networking virtualization. We have VCP number 94, so we've been doing that from the very beginning. But about six years ago, we realized that IT was changing, that business was changing, that the demands of the customers was changing and we needed to create the full stack message and a full-stack practice. So we hired data scientists and developers in DevOps, MLOps and gave them the environments and the tools that they could use to build experience around AI, ML deep learning. So now when we engage with our customers, not only can we handle the entire enterprise stack that they have, but we can help accelerate them on their adoption of open-source technologies, cloud native development and AI and integrating that into their business processes. >> I love it. You got to keep moving. You've been around for a long time, but you're not just sitting still. I wonder if you could comment in an Eric, I want you to comment as well. From your customer's perspective Stan, what are the big trends that you see that are impacting their business and the challenges that they're facing? >> Yeah, that's great. So kind of ties into what I just said. Today we live in a data-driven society. Everything that we do is really driven by how the customer wants to engage. And that's both an internal customer and your end user customers, on how they want to engage, how they want to consume and how they want to interact with everything out there in the world, right? So the real trends is really around engaging with the customer, but that means that you need to be data-driven, you need to adopt AI platforms, you need to adopt a more holistic view of what you're doing with your customers. That drives up the importance of the data that you have in your shop, right? So then cybersecurity becomes extremely important, not just because of the technical skills of the hacker is getting better and better, but because we're becoming more reliant on the data that we have moving forward and we're proud to partner with Infinidat in leveraging InfiniGuard and Infinni safe to really protect our customer's data. >> Great. Eric, thinking about the trends and some of the issues that Stan just mentioned, when you think about the launch and the announcement that you just made, how do you see it fitting in to Stan's business? How's how it's going to help the end customers? >> Well, I think there's one key aspect. As noted in the fortune survey of CEOs in 2021. The number one concern of CEOs of the fortune 500, was cybersecurity and they saw that as biggest threat to their business. As Stan pointed out, that becomes of the importance of the digital data, that all companies generate, of all types, financial services, healthcare, government institutions, manufacturing, you name it. So one of the key things you've got to do, is make sure that your storage estate, fits into an overall cybersecurity strategy. And with InfiniGuard, or Ifini safe technologies, we can ensure that Stan's customers and customers of our other business partners all over the world, can make sure that the data is safe, protected and can help them form a malware or ransomware attack, against that valuable data set. >> Well then you know, one of you guys could come with, I mean, we talked to CSOs and they've told us that there be could in part due to the pandemic, largely actually, their whole strategy has changed. Their spending strategies changed, no longer than just sort of putting up hardware firewalls. They're shifting their focus to two different areas, obviously endpoint, you know, cloud security is a big deal, identity access management, but ransomware, is just top of mind for everybody. And as we talked about earlier, the exposure, now the weak links, whether you're working from home, or Stan you mentioned greater sophistication of hacker. So what are you hearing from customers in this regard, Stan? >> Well, you know I think you have that, right? But then you always have, we've been doing this for 26 years. I've never heard of an IT budget that that's gone up, in any year, right? So, with the sophistication of these hackers that are coming out and the different angles that they're using to get in, it is extremely important for our customers to be very efficient and choose their security strategy and products very wisely, right? I think I read an article a year or so ago that the average enterprise had like something like 27 different security products and imagine a CSO and his team, who is struggling with their budget to manage that. So for us to be able to leverage InfiniGuard and Infini safe and to be able to provide, you know the immutable snapshots. The logical air gas, the physical air backs and offense network for recovery. That's all extremely easy to manage. I mean I talked to my customers on why they have chosen Infinidat, you know through us, right? And one of the things that they always talk about is how easy and how amazing the support is. How easy it is to install, how easy it is to manage. And normally when you have a simple product, right, you think you can sell that to an unsophisticated customers. But my most technical customers really appreciate this, because of the way Infinidat manages itself and provides the tools saying, just for example, the host tools, right? It does it in the way that they do it, so they trust it, so that they can focus on the more important tasks, rather than the tier and feeding other storage environment. >> Yeah, thank you and then when you talk to CSOs, you ask them what's the number one problem, they'll tell you lack of talent and you just nailed it. You've got on average 27 different tools, new tools coming out every day, you're getting billion dollar, VC investments and more and more companies are getting into it. It just adds to that confusion. So Stan, I wonder if you could talk about, specifically InfiniGuard, how it fits into your stack like where and how you're applying it? Maybe you could talk about some specific use cases. >> Oh yeah definitely, you know we have customers in pretty much every vertical, that we're supporting their stores environments and Infinidat plays and all of those verticals with all of our customers. One in particular a healthcare account, one of our very first Infinidat customers and over the years, is become the de facto standard, stores platform that they have. And they also now have InfiniGuard as the backup target for commovault. And this is one of those examples of the very technical discerning customer, that really demands excellence, right? So they love, you know, the three controller setup versus a dual controller set up, they love the availability and the resiliency, but then when it comes to the cybersecurity, before they moved on to this platform, they did have some ransomware attacks and they did have to pay out and it was very public. And, you know, since they've gone onto this platform, they feel much more comfortable. >> Excellent. So Eric, I want to bring you in. So let's talk through some of the options that customers have. You and I were talking earlier about, you know, the local air gap, what is that? You know, the logical air gap if you will and then the physical labor, what patterns are you seeing with customers to really try to protect themselves against some of this ransomware? How are they approaching it? >> Well, first of all, obviously, we with the InfiniGuard, has a purpose built backup appliance can work with all the various backup vendors. But because backup, is one of the first things these sophisticated ransomware, or malware it entity is going to attack. right? Otherwise the CIO will just call up say, hey, do we have a good backup? Let's recover from that. So secondary storage, AK their backup estate, is exactly the first thing they're going to target. And they do it certain viciously of course. So what are the key things we do, is we allow them to take those backup datasets, commvault for example and in Stan's example, or Vain or veritas or IBM Spectrum Protector, many other packages, even directly with databases like with Oracle Armin and allow them to create a mutable snapshots. Can't delete them, can't change them, can alter them. And then we air gap them locally, from the management framework. So in an InfiniGuard, we have a technology known as our day-to-day dupe engines ODDES. Those are really the management scanner for the entire solution. So when we create an immutable snapshots, we create a logical air gap, with ODDES, cannot alter the immutability characteristics, they cannot shorten them, they can not lengthen them, in short we take that management scheme away and create this separation. But we also allow them to replicate those backup datasets to a remote InfiniGuard box. You would set up the exact same parameters, I want to make an immutable snap every day, every 12 hours, every six hours and then you've got the duplicate. Remember the average length, from breach to closure on a cyber attack is 287 days. So once the attack starts, you don't know until they ask you for the ransom, it could be going on for 50 days, a hundred days, 150 days. And it's all done, if you will on the download, hidden. So if by the way, you happen to have a data center fire, or you happen to have a tornado or an earthquake, or some other natural disaster, you still want that data replicated to a secondary site, but then you still want the capability of the cyber resilience, as Stan pointed out. So you can do that. We can create a then a isolated fence network and we can do that on one InfiniGarden. Most of our competitors require two data protection appliances and it's public it's right on their websites. So we save you on some CapEx there and then we can do this near instantaneous recovery. And that's not just of the dataset. Some of the cyber reasons, technology you'll see out there, including on primary storage, only recovers the dataset. We can recover the entire backup data set and all the surrounding environment. So to second that Vain or Veritas, IBM spectrum protect commvault, backup is available. The backup admins or the storage admins, could immediately restored, it's ready to go. And we can do that in 15 to 30 minutes. Now that is being fast to react to a problem. >> So thank you for that. So Stan, I wonder if you could talk about the best practice Eric was just sharing, the local air gap and then the secondary, is that really in the case of a disaster, or is it also to isolate the network? What are you seeing as the gold standard that customers are applying with your advice? >> Yeah, definitely the gold standard would be three sites. We do have a lot of our customers. The one healthcare customer in particular is splits it between two sides and they are actually working with us right now to architect the third site. Just for that fact, we are down in Texas, hurricanes can come in 60, 70, 80 miles on in land. And then there's, you know, hurricane Harvey, right with all the flooding and stuff like that. So they do want to set up a third side. I think that gives them the peace of mind. And you know the whole thing about it is right. You know, having an environment like this means the CSO and his team can focus on preventing attacks, while they're very confident that their infrastructure team, can handle anything that slips by them. >> Okay, great. Thank you. We're about out of time but Eric, I wonder if you could kind of bring us home, give us a summary of, how you see InfiniGuard impacting customers, you know where's that value that business case for them. I wonder if you could just tie that note for us. >> Sure. We want to make sure that we tie everything back, normally technical value, as Stan very eloquently did with several different customers, but what we can do from a business value perspective. So as an example, one of our infiniGuard customers, is a global financial services company and they were using a solution from a different purpose-built backup appliance provider. They switched to us, not only they're able to increase the number of daily backups, from 30,000 to 90,000. So they get better data protection, but on top of that, they cut 40% of their costs. So you want to make sure that while you're doing this, you're doing things like consolidation. One of our other customers, which is in EMEA, in the European area, they had 14 purpose-built backup appliances, seven in one data center and set seven and a second data center. Now they've got two, one in one data center, one of the other, they of course do the local backups right then and there. And then they replicate, from one data center to the other data center. As both data centers are both active data centers, but differ for the other data center. So from their perspective, dramatic reduction of OPEX and CapEx, 14 physical boxes down to two. And of course the associated management of both the manpower side, but why I love to call the watch slots, power and floor. All of those things that go into an OPEX budget, they were cut dramatically, 'cause there's only two systems now, to power cool, et cetera et cetera. Floor space, Rackspace from 14. So wow, did they save money. So I think, it's not only providing that data protection and cyber resilience technology, but doing it in a cost-effective way. And as Stan pointed out, in a highly automated way, that cuts back on the manpower they need to manage these systems, because they're overworked and they need to focus on as Stan pointed out, their AI infrastructure, where they're doing for AI applications, don't have time to deal with it. So the more we automate, the better it is for them and the easier it is for everyone from the end-user perspective, as well as up in through their entire IT chain of command. >> Okay, if you want more information, you can go to infinidatguard.com or it's markiisis.com and check it out, learn about their full stack solution. A little bit about AI. Gentlemen, thanks so much for the conversation today, great to have you. >> Mark and Steve: Thank you, Dave. Now in a moment, I'm going to have some closing thoughts on the market and what we heard today. Thank you for watching the cube. You're a leader in enterprise tech coverage.

>>From around the globe. It's the Cube covering data citizens 21 brought to you by culebra. Hello everyone john walls here as we continue our cube conversations here as part of Data citizens 21 the conference ongoing caliber at the heart of that really at the heart of data these days and helping companies and corporations make sense. All of those data chaos that they're dealing with, trying to provide new insights, new analyses being a lot more efficient and effective with your data. That's what culebra is all about and their founder and their Chief data Citizen if you will stand christians joins us today and stan I love that title. Chief Data Citizen. What is that all about? What does that mean? >>Hey john thanks for having me over and hopefully we'll get to the point where the chief data citizen titlists cleaves to you. Thanks by the way for giving us the opportunity to speak a little bit about what we're doing with our Chief Data Citizen. Um we started the community, the company about 13 years ago, uh 2008 and over those years as a founder, I've worn many different hats from product presales to partnerships and a bunch of other things. But ultimately the company reaches a certain point, a certain size where systems and processes become absolutely necessary if you want to scale further for us. This is the moment in time when we said, okay, we probably need a data office right now ourselves, something that we've seen with many of our customers. So he said, okay, let me figure out how to lead our own data office and figure out how we can get value out of data using our own software at Clear Bright Self. And that's where it achieved. That a citizen role comes in on friday evening. We like to call that, drinking our own champagne monday morning, you know, eating our own dog food. But essentially um this is what we help our customers do build out the offices. So we're doing this ourselves now when we're very hands on. So there's a lot of things we're learning again, just like our customers do. And for me at culebra, this means that I'm responsible as achieved data citizen for our overall data strategy, which talks a lot about data products as well as our data infrastructure, which is needed to power data problems now because we're doing this in the company and also doing this in a way that is helpful to our customers. Were also figuring out how do we translate the learning that we have ourselves and give them back to our customers, to our partners, to the broader ecosystem as a whole. And that's why uh if you summarize the strategy, I like the sometimes refer to it as Data office 2025, it's 2025. What is the data office looked like by then? And we recommend to our customers also have that forward looking view just as well. So if I summarize the the answer a little bit it's very similar to achieve their officer role but because it has the external evangelization component helping other data leaders we like to refer to it as the chief data scientist. >>Yeah that that kind of uh you talk about evangelizing obviously with that that you're talking about certain kinds of responsibilities and obligations and when I think of citizenship in general I think about privileges and rights and about national citizenship. You're talking about data citizenship. So I assume that with that you're talking about appropriate behaviors and the most uh well defined behaviors and kind of keep it between the lanes basically. Is that is that how you look at being a data citizen. And if not how would you describe that to a client about being a data citizen? >>It's a very good point as a citizen. You have the rights and responsibilities and the same is exactly true for a day to citizens. For us, starting with what it is right for us. The data citizen is somebody who uses data to do their job. And we've purposely made that definition very broad because today we believe that everyone in some way uses data, do their job. You know, data universal. It's critical to business processes and its importance is only increasing and we want all the data citizens to have appropriate access to data and and the ability to do stuff with data but also to do that in the right way. And if you think about it, this is not just something that applies to you and your job but also extends beyond the workplace because as a data citizen, you're also a human being. Of course. So the way you do data at home with your friends and family, all of this becomes important as well. Uh and we like to think about it as informed privacy. Us data citizens who think about trust in data all the time because ultimately everybody's talking today about data as an asset and data is the new gold and the new oil and the new soil. And there is a ton of value uh data but it's not just organizations themselves to see this. It's also the bad actors out there were reading a lot more about data breaches for example. So ultimately there is no value without rescue. Uh so as the data citizen you can achieve value but you also have to think about how do I avoid these risks? And as an organization, if you manage to combine both of those, that's when you can get the maximum value out of data in a trusted manner. >>Yeah, I think this is pretty interesting approach that you've taken here because obviously there are processes with regard to data, right? I mean you know that's that's pretty clear but there are there's a culture that you're talking about here that not only are we going to have an operational plan for how we do this certain activity and how we're going to uh analyze here, input here action uh perform action on that whatever. But we're gonna have a mindset or an approach mentally that we want our company to embrace. So if you would walk me through that process a little bit in terms of creating that kind of culture which is very different then kind of the X's and oh's and the technical side of things. >>Yeah, that's I think where organizations face the biggest challenge because you know, maybe they're hiring the best, most unique data scientists in the world, but it's not about what that individual can do, right? It's about what the combination of data citizens across the organization can do. And I think there it starts first by thinking as an individual about universal goal Golden rule, treat others as you would want to be treated yourself right the way you would ethically use data at your job. Think about that. There's other people and other companies who you would want to do the same thing. Um now from our experience and our own data office at cordoba as well as what we see with our customers, a lot of that personal responsibility, which is where culture starts, starts with data literacy and you know, we talked a little bit about Planet Rock and small statues in brussels Belgium where I'm from. But essentially um here we speak a couple of languages in Belgium and for organizations for individuals, Data literacy is very similar. You know, you're able to read and write, which are pretty essential for any job today. And so we want all data citizens to also be able to speak and read and write data fluently if I if I can express it this way. And one of the key ways of getting that done and establishing that culture around data uh is lies with the one who leads data in the organization, the Chief Petty Officer or however the roll is called. They play a very important role in this. Um, the comparison maybe that I always make there is think about other assets in your organization. You know, you're you're organized for the money asset for the talent assets with HR and a bunch of other assets. So let's talk about the money asset for a little bit, right? You have a finance department, you have a chief financial officer. And obviously their responsibility is around managing that money asset, but it's also around making others in the organization think about that money asset and they do that through established processes and responsibilities like budgeting and planning, but also ultimately to the individual where, you know, through expense sheets that we all off so much they make you think about money. So if the CFO makes everyone in the company thinks about think about money, that data officer or the data lead has to think has to make everyone think uh in the company about data as a as it just as well and and those rights those responsibilities um in that culture, they also change right today. They're set this and this way because of privacy and policy X. And Y. And Z. But tomorrow for example as with the european union's new regulation around the eye, there's a bunch of new responsibilities you have to think about. >>Mhm. You know you mentioned security and about value and risk which is certainly um they are part and parcel right? If I have something important, I gotta protect it because somebody else might want to um to create some damage, some harm uh and and steal my value basically. Well that's what's happening as you point out in the data world these days. So so what kind of work are you doing in that regard in terms of reinforcing the importance of security, culture, privacy culture, you know this kind of protective culture within an organization so that everybody fully understands the risks. But also the huge upsides if you do enforce this responsibility and these good behaviors that that obviously the company can gain from and then provide value to their client base. So how do you reinforce that within your clients to spread that culture if you will within their organizations? >>Um spreading a culture is not always an easy thing. Um especially a lot of organizations think about the value around data but to your point, not always about the risks that come associated with it sometimes just because they don't know about it yet. Right? There's new architecture is that come into play like the clouds and that comes with a whole bunch of new risk. That's why one of the things that we recommend always to our uh customers and to data officers and our customers organizations is that next to establishing that that data literacy, for example, and working on data products is that they also partners strongly with other leaders in their organization. On the one hand, for example, the legal uh folks, where typically you find the aspects around privacy and on the other hand, um the information security folks, because if you're building up a sort of map of your data, look at it like a castle, right that you're trying to protect. Uh if you don't have a map of your castle with the strong points and weak points and you know, where people can build, dig a hole under your wall or what have you, then it's very hard to defend. So you have to be able to get a map of your data. A data map if you will know what data is out there with being used by and and why and how and then you want to prioritize that data which is the most important, what are the most important uses and put the appropriate protections and controls in place. Um and it's fundamental that you do that together with your legal and information security partners because you may have as a data leader you may have the data module data expertise, but there's a bunch of other things that come into play when you're trying to protect, not just the data but really your company on its data as a whole. >>You know you were talking about 2025 a little bit ago and I think good for you. That's quite a crystal ball that you have you know looking uh with the headlights that far down the road. But I know you have to be you know that kind of progressive thinking is very important. What do you see in the long term for number one? You're you're kind of position as a chief data citizen if you will. And then the role of the chief data officer which you think is kind of migrating toward that citizenship if you will. So maybe put on those long term vision uh goggles of yours again and and tell me what do you see as far as these evolving roles and and these new responsibilities for people who are ceos these days? >>Um well 2025 is closer than we think right? And obviously uh my crystal ball is as Fuzzy as everyone else's but there's a few things that trends that you can easily identify and that we've seen by doing this for so long at culebra. Um and one is the push around data I think last year. Um the years 2020, 2020 words uh sort of Covid became the executive director of digitalization forced everyone to think more about digital. And I expect that to continue. Right. So that's an important aspect. The second important aspect that I expect to continue for the next couple of years, easily. 2025 is the whole movement to the cloud. So those cloud native architecture to become important as well as the, you know, preparing your data around and preparing your false, he's around it, et cetera. I also expect that privacy regulations will continue to increase as well as the need to protect your data assets. Um And I expect that a lot of achieved that officers will also be very busy building out those data products. So if you if you think that that trend then okay, data products are getting more important for t data officers, then um data quality is something that's increasingly important today to get right otherwise becomes a garbage in garbage out kind of situation where your data products are being fed bad food and ultimately their their outcomes are very tricky. So for us, for the chief data officers, Um I think there was about one of them in 2002. Um and then in 2019 ISH, let's say there were around 10,000. So there's there's plenty of upside to go for the chief data officers, there's plenty of roles like that needed across the world. Um and they've also evolved in in responsibility and I expect that their position, you know, it it is really a sea level position today in most organizations expect that that trend will also to continue to grow. But ultimately, those achieved that officers have to think about the business, right? Not just the defensive and offensive positions around data like policies and regulations, but also the support for businesses who are today shifting very fast and we'll continue to uh to digital. So those Tv officers will be seen as heroes, especially when they can build out a factory of data products that really supports the business. Um, but at the same time, they have to figure out how to um reach and always branch to their technical counterparts because you cannot build that factory of data products in my mind, at least without the proper infrastructure. And that's where your technical teams come in. And then obviously the partnerships with your video and information security folks, of course. >>Well heroes. Everybody wants to be the hero. And I know that uh you painted a pretty clear path right now as far as the Chief data officer is concerned and their importance and the value to companies down the road stan. We thank you very much for the time today and for the insight and wish you continued success at the conference. Thank you very much. >>Thank you very much. Have a nice day healthy. >>Thank you very much Dan Christians joining us talking about chief data citizenship if you will as part of data citizens 21. The conference being put on by caliber. I'm John Wall's thanks for joining us here on the Cube. >>Mhm.

>> - From around the globe, it's the cube covering data citizens, 21 brought to you by Collibra. >> Hello, everyone, John Walls here, As we continue our cube conversations here as part of data citizens, 21, the conference ongoing. Collibra at the heart of that, really at the heart of data these days and helping companies and corporations make sense. Although this data chaos that they're dealing with, trying to provide new insights, new analysis being a lot more efficient and effective with your data. That's what Collibra is all about. And their founder and their chief data citizen, if you will, Stan Christiaens joins us today. And Stan, I love that title, chief data citizen. What does that all about? What does that mean? >> Hey John, thanks for having me over. And hopefully we'll get to a point where the chief data citizen Titelist cleaves to you. Thanks by the way, for giving us the opportunity to speak a little bit about what we're doing with our chief data citizen. We started the company about 13 years ago, 2008. And over those years, as a founder I've worn many different hats from product to pre-sales to partnerships and a bunch of obvious things. But ultimately the company reaches a certain point a certain size where systems and processes become absolutely necessary if you want to scale further. And for us, this is the moment in time where we said, okay we probably need a data office right now ourselves, something that we've seen with many of our customers. So we said, okay, let me figure out how to lead our own data office and figured out how we can get value out of data using our own software at Collibra itself. And that's where the chief data citizen role comes in. On Friday evening, we like to call that drinking our own champagne moment morning, either eating our own dog food but, essentially this is what we help our customers do, build out the data offices. So we're doing this ourselves now, when we're very hands-on. So there's a lot of things that we're learning, again just like our customers do. And for me, at Collibra, this means that I'm responsible as a chief data citizen for our overall data strategy, which talks a lot about data products, as well as our data infrastructure, which is needed to power data products. Now, because we're doing this in the company and also doing this in a way that is helpful to our customers. We're also figuring out how do we translate the learnings that we have ourselves and give them back to our customers, to our partners, to the broader ecosystem as a whole. And that's why if you summarize the strategy, I like to sometimes refer to it as data office 2025, it's 2025. What is the data office look like by then? And we recommend to our customers to also have that forward looking view just as well. So if I summarize the, the answer a little bit and it's fairly similar to achieve that officer role but, because it has the external evangelization component, helping other data leaders, we like to refer to it as the chief data citizens. >> Yeah, and that, that kind of, you talked about evangelizing, obviously with that, that you're talking about certain kinds of responsibilities and obligations. And I, when I think of citizenship in general I think about privileges and rights and you know, about national citizenship. You're talking about data citizenship, So I assume that with that you're talking about appropriate behaviors and the most well-defined behaviors, and kind of keeping it between the lanes basically. Is that, is that how you look at being a data citizen or, and if not, how would you describe that to a client about being a data citizen? >> It's a very good point, as a citizen you have rights and responsibilities, and the same is exactly true for a data citizen. For us, starting with what it is, right for us, A data citizen is somebody who uses data to do their job. And we've purposely made that definition very broad because today we believe that everyone in some way uses data to do their job. You know, data is universal. It's critical to business processes and it's importance is only increasing. And we want all the data citizens to have appropriate access to data and the ability to do stuff with data but, also to do that in the right way. And if you think about it this is not just something that applies to you in your job but, also extends beyond the workplace because as a data citizen, you're also a human being, of course. So, the way you do data at home with your friends and family, all of this becomes important as well. And we like to think about it as informed privacy aware, data citizens should think about trust in data all the time, because ultimately everybody's talking today about data as an asset, and data is the new gold, and the new oil, and the new soil, and there is a ton of value in data but, as much as organizations themselves to see this, it's also the bad actors out there. We're reading a lot more about data breaches, for example. So, ultimately there's no value without risk. So, as a data citizen, you can achieve a value but, you also have to think about, how do I avoid these risks, and as an organization, if you manage to combine both of those, that's when you can get the maximum value out of data in a trusted manner. >> Yeah, I think this is pretty, an interesting approach that you've taken here because obviously there there are processes with regard to data, right? I mean, the, you know, that that's pretty clear but, there are also, there's a culture that you're talking about here that, that not only are we going to have an operational plan for how we do this certain activity and how we're going to analyze here, input here, action, or perform action on that, whatever but we're going to have a mindset or an approach mentally that we want our company to embrace. So, if you would walk me through that process a little bit in terms of creating that kind of culture, which is very different than kind of the X's and O's and the technical side of things. >> Yeah. That's I think when organizations face the biggest challenge, because, you know maybe they're hiding the best most unique data scientists in the world but, it's not about what that individual can do, right? It's about what the combination of data citizens across the organization can do. And I think it starts first by thinking as an individual about universal goal, golden rule, treat others as you would want to be treated yourself, right? The way you would ethically use data at your job. Think about that, There's other people at other companies, who you would want to do the same thing. Now, from our experience, in our own data office at Collibra, as well as what we see with our customers. A lot of that personal responsibility which is where culture starts, starts with data literacy. And, you know, we talked a little bit about Plymouth rock and the small statues in Brussels Belgium, where I'm from but, essentially here we speak a couple of languages in Belgium. And for organizations, for individuals data literacy is very similar. You know, you're able to read and write which are pretty essential for any job today. And so we want all data citizens to also be able to speak and read and write data fluently. If I, if I can express it this way. And one of the key ways of getting that done and establishing that culture around data, lies with the one who leads data in the organization, the chief data officer, or however the role is called. They play a very important role in this. In comparison, maybe that I always make there is think about other assets in your organization. You know, you're organized for the money assets, for the talent assets, with HR and a bunch of other assets. So let's talk about the, the money assets for a little bit, right? You have a finance department, you have a chief financial officer, and obviously their responsibility is around managing that money asset. But it's also around making others in the organization think about that money. And they do that through established processes and responsibilities like budgeting and planning but, also ultimately to the individual where, you know, through expense sheets that we all love so much, they make you think about money. So, if the CFO makes everyone in the company thinks about think about money, that data officer, or the data lead, has to think, has to make everyone think in the company about data assets, asset, just as well. And those rights, those responsibilities in that culture, they also change, right? Today, they're set this and this way because of privacy and policy X and Y and Z. But tomorrow, for example, as, as with the European union's new regulation around BI, there's a bunch of new responsibilities you'll have to think about. >> You mentioned security and about value and risk, which is certainly, they are part and parcel, right? If I have something important I've got to protect it because somebody else might want to, to create some damage, some harm and and steal my value, basically when that's, what's happening as you point out in the data world these days. So, so what kind of work are you doing in that regard in terms of reinforcing the importance of security culture, privacy culture, you know, this kind of protective culture within an organization so that everybody fully understands, you know, the risks but, also the huge upsides. If you do enforce this responsibility and these good behaviors that that obviously the company can gain from, and then provide value to their client base. So how do you reinforce that within your clients to spread that culture, if you will, within their organizations? >> Spreading a culture is not always an easy thing, And especially a lot of organizations think about the value around data, but to your point, not always about the risks that come associated with it. Sometimes just because they don't know about it yet, right, there's new architectures that come into play, like the clouds and that comes with a whole bunch of new risks. That, that's why one of the things that we recommend always to our customers and to data officers in our customer's organizations, is that next to establishing that, that data literacy, for example, and working on data products is that they also partner strongly with other leaders in their organization. On the one hand, for example, the legal folks, where typically you find the the aspects around privacy and on the other hand, the information security folks, because if you're building up sort of map of your data, look at it like a castle, right, that you're trying to protect. If you don't have a map of your castle, with the strong points and the weak points, and you know where people can build, dig a hole under your wall or what have you, then it's very hard to defend. So, you have to be able to get a map of your data, a data map if you will, know what data is out there. Who its being used by, and why and how, and then you want to prioritize that data, which is the most important what are the most important uses and put the appropriate protections and controls in place. And it's fundamental that you do that together with your legal and information security partners because you may have as a data lead that you may have the data knowledge, the data expertise but, there's a bunch of other things that come into play when you're trying to protect, not just the data but, really your company on its data as a whole. >> No, you Were talking about 2025 a little bit ago, and I thought good for you, that's quite a crystal ball that you have it, you know looking to, you know, with the headlights that far down the road, but I know you have to be, you know that kind of progressive thinking is very important. What do you see in, in the long-term for number one, your kind of position as a chief data citizen, if you will, and then the role of the chief data officer, which you think is kind of migrating toward that citizenship, if you will. So, maybe put on those long-term vision goggles of yours again, and tell me, what do you see as far as these evolving roles and, and these new responsibilities for people who are CEOs these days? >> Well, 2025 is closer than we think right? Then obviously, my crystal ball is as fuzzy as everyone else's but, there's a few things, that trends that you can easily identify and that we've seen by doing this for so long at Collibra. And one is the, the push around data. I think last year, the years, 2020,` where sort of COVID became the executive director of digitalization. Forced everyone to think more about digital, and I expect that to continue. So, that's an important aspect. The second important aspect that I expect to continue for the next couple of years, easily in 2025 is the whole movement to the cloud. So these cloud native architectures become important, as well as the, you know, preparing your data around it, preparing your policies around it, etc.. I also expect that privacy regulations will continue to increase as well as the needs to protect your data assets. And I expected a lot of key data officers will also be very busy building out those data products. So if you, if you take that that trend then, okay data products are getting more important for key data officer's, then data quality is something that's increasingly important today to get right, otherwise, becomes a garbage in garbage out kind of situation, where your data products are being fed bad foods and ultimately their outcomes aren't very clear. So for us, for the chief data officers, I think it was about one of them in 2002, and then 2019 ish, let's say there were 10,000. So there's plenty of upsides for the chief data officer there's plenty of roles like that needed across the world. And they've also evolved in, in responsibility. And I expect that their position, you know, as it it is really a C-level position today in most organizations. Expect that, that trend will also continue to grow. But ultimately those chief data officers have to think about the business, right? Not just the defensive and offensive positions around data, like almost policies and regulations but, also the support for businesses who are today, shifting very fast and will continue to, to digital. So, those key data officers will be seen as key notes. Especially when they can build out the factory of data products that really supports the business. But at the same time, they have to figure out how to reaching all of the branch to their technical counterparts, because you cannot build a factory of data products in my mind at least, without the proper infrastructure. And that's where your technical teams come in. And then obviously the partnerships with your video and information security folks, of course. >> Well heroes, everybody wants to be the hero. And I know that's a, you painted a pretty clear path right now, as far as the chief data officer's concerned and their importance and the value to companies down the road. Stan, we thank you very much for the time today and for the insight, and wish you continued success at the conference. Thank you very much. >> Thank you very much. Have a nice day. Stay healthy. >> Thank you very much Stan Christiaen's joining us, talking about chief data citizenship, if you will, as part of data citizens, 21 the conference being put on by Collibra. I'm John Walls. Thanks for joining us here on the cube. (upbeat music)

>> Announcer: From San Francisco, it's the Cube, covering Samsung Developer Conference 2017, brought to you by Samsung. (electronic music) >> Hello, everyone, welcome back, live here in San Franscisco, Moscone West. This is the Cube's exclusive coverage of Samsung's Developer Conference. I'm John Furrier, the co-founder of SiliconANGLE Media, cohost here in the Cube. My next guest is Paris Rain, recording artist, innovator, working with Stan Lee, music projects. What's exciting about this event is that you have such exciting new lifestyle trends happening and this one here's a great story. Welcome to the Cube. >> Thank you very much. It's nice being here with everybody. >> You look fabulous, you're a superhero. Tell us the story, because one of the things that's super compelling about your projects you're working on, and your innovation, is the convergence of culture. You've got Comic Con kind of culture integrated with music, online services, digital communities, and now new products are being developed, new experiences, AR, VR, the new vibe is out there. Tell your story. >> Well, we just thought, why not? So what happened was, my manager had a really close relationship to Stan and he basically showed Stan my music and said, "Hey, this girl's talented," and then we got to talking and we were like, "Why don't we integrate Stan into the music business?" He took over the movie industry, why doesn't he take over the music industry as well? >> And so Marvel obviously absolutely hits a home run, the comics, but this is now also a digital life, and so people look at all the successes, certainly the movies. >> Absolutely, yeah, that would be the biggest. >> I was a comic kid when I was growing up. But the movies have just been spectacular. One sequel after the other. Gaming now is part of the movie scene, so gaming culture is huge, and you're doing a game with Samsung, that's something you've got going on, what's that about? >> I can't say too much about it, to be honest with you, but we're in preparation with Samsung on this new, innovative, high tech, app that's coming out, and it's going to be integrated to, I mean, everything's going to come together, it's going to have my music in it, it's going to have, Stan's going to make a cameo, in that, in the game, and in my music video as well, and yeah it's all coming together. >> So that's coming out. You can't really talk, it's under wraps, but it's an integrated project. You've been successfully into viral videos, a couple years ago that went viral on YouTube. What's that like, do you just like wake up one day and say, "Oh my God, this is going crazy?" >> It kind of happened like that with YouTube. Because you do it all yourself. I worked with Afflux Studios, it's in Wellington. They're a really awesome studio, super high tech and I got kind of an in, they're kind of family to me, and so it was kind of ... It was really easy to get with them anyway so we were like, "Hey, I did the blue hair thing." And I was like, "You know what? "I'm set on going viral, this is what I want to do." And the first video I put out, bitch better have-- B better have my money. (John laughs) By Rihanna. >> We're the internet. You can say whatever you want. >> Oh, fuck it. Bitch better have my money. Oh shit, really, I can swear? Oh I feel so much more comfortable now. On stage, I felt so ... So yeah, "Bitch Better Have My Money" came out and it got like 1.5 million, or 1.3 million views, and then I did another video and it got another 1.3 million. >> All right, so what happens after, because everyone wants to know. 'Cause everyone tries to engineer viral, and you can't really engineer viral, 'cause viral is one of those things where-- >> Dye your hair blue, sell your soul. >> (laughs) Okay, you sold your soul. Who bought it? The Devil? (laughs) >> The Devil, yeah, the Devil bought it. No. >> Well, you got to tell. >> No, for real, like honest talk right now. What you have to do is go on the top charts and pick one of your favorites, something that is completely not you, or you, but you have to do it a different way, so what we did, was I work with a producer who's super awesome, his name's Arcaeus, and we remixed it. And you know how remixes are huge? So we were like, "Why don't we do a remix cover?" and then it blew up and that's what happened. >> So now that you're on Stan's radar, he's got the whole, you know, he's been around the block, he's a legend in the community. His success is off the charts. What's his creative mind like right now? How are you guys looking at the mark offs? You're integrating music with comics. >> With comics and with gaming, that's, I mean, you just nailed it. >> So what's the creative scene like, do you guys sit back, do you kick back? What do you talk about? >> Stan's really big on making the powers unique, and he always has been really great on making sure that the powers are unique, so that's right now, we're still in the preparation stage of everything, but we're, we want to, we're prepping with Marvel right now. I have to say all the right words in order to not get in trouble. >> PR handled. (they laugh) >> We're prepping with Marvel to go into one of their storylines that I can't say. I can't say too much. >> Yeah. All these licensing things are going on. I've always been fascinated with how it's about time that the comics and Marvel really start expanding and start franchising the gaming because we were talking yesterday with one of the guests influencers about how the gaming culture really is a precursor to how life is evolving. You got multiplayer, it is virtual, you got virtual currencies, you have things happen on gaming, so it's a natural extension to move into gaming. How does the music piece, I mean, do you guys have licensing stuff? You must have to get authorizations. Is it indie, what's ... >> Well, it would be my music that's on the game. >> So you're doing your own music for the game. >> So I'd just be paying myself, essentially. >> You're licensing your movie? >> Yeah. >> All right. So here's another question for you. What's the weirdest thing that's happened to you in the past year? >> This interview right here. No, I'm just joking. >> (laughs) It's great for me too. >> No, it's Stan calling me up and saying, "Hey, I want to make you a superhero." That's the weirdest thing I've ever gone through. >> What's it like in the L.A. scene for you? >> I don't go to L.A. too much. I don't, but I am moving out there next month, so I will be in the L.A. scene. The L.A. scene's crazy, from what I've seen, from what I've seen about the scene. Yeah, it's crazy. >> So what's the plans for you and Stan the next couple months? What are you guys going to be working on, heading down, doing the tour, creative-- >> I think we're going to a couple Comic Cons. Potentially getting inducted into the music industry by a big player in the hiphop culture who, I can't say his name. There's a lot of big things, but it's mainly just preparation right now, we're just talking about everything, what we all want to do, and making sure that the gaming app with Samsung, which is why we're here today, it's like that's a huge thing, Jackie, Jacqueline Chow whose mobile game, it's a mobile game, so the game, the music, and hopefully eventually movies, but and the comic books, oh! You know what I think is really cool? I think that we're going to do a comic book on like a tablet version or a mobile version of the comic books, and I don't know if you've seen, I forget what it's called, but it's like a tilt screen comic book that's really, it's really innovative? I'll have to show you the app after, but it's, I think we're going to do something like that, 'cause people don't buy comic books, people don't buy books, they don't go to the store, they don't go to the library, I mean, I do, but they don't, you know? They go on their phone and they pay for it. >> Phone is where the action is, for the kids. All right, so what's exciting you these days? Obviously, you must be pretty pumped. Things are rocking. >> Yeah. >> What's on your mind these days? >> What's on my mind these days? >> Yeah, what are you excited about? >> Sitting beside Stan and just talking about this stuff. Honestly, performing, I'm super excited about the show, 'cause I want the show to be, I mean, if I'm a superhero, it's got to be heroic. >> Can you share your superpowers? What's the ... >> I can't! I can't, but I am a singer so I think obviously we're going to roll with the singing 'cause I think, I mean, naturally singing, performing, I think is almost like a human superpower that we have. >> So what's the event? Give us your take on the event here. Obviously Samsung is a big part, and congratulations, nice gig to have there. Congratulations, so you've got the app coming on, we'll dig into that, we'll look forward to the news when it comes out. But the vibe here, this developer community. We see high school kids here, I saw some eight year olds here. I mean, this is like an awesome developer conference. >> It is! When I was on stage with Stan, it was like, we had five minutes left, and I was kind of, you know, we had gone through all of the questions that we'd prepared, and I was like, "Hey, guys, if anyone "has any questions, please raise your hand," or whatever, and just kids, it was all, it was like mostly kids at first and then the adults are like, oh well we can do too, but the kids were like, "Stan, what do you think about DC?" and he was like, "DC who?" It was hilarious. >> So next year, "Rain, what do you think about ..." So you're going to be popular, congratulations. Thank you for coming on and chatting with me. This was great, with Rain Paris, here at the Cube live, from San Francisco for SDC, you got games coming out, music converging with comics, this is the culture. More after this short break. (electronic music)

>> From the Cube Studios in Palo Alto in Boston, bringing you data-driven insights from The Cube and ETR. This is "Breaking Analysis" with Dave Vellante. >> The world's leading telcos are trying to shed the stigma of being monopolies lacking innovation. Telcos have been great at operational efficiency and connectivity and living off of transmission, and the costs and expenses or revenue associated with that transmission. But in a world beyond telephone poles and basic wireless and mobile services, how will telcos modernize and become more agile and monetize new opportunities brought about by 5G and private wireless and a spate of new innovations and infrastructure, cloud data and apps? Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this breaking analysis and ahead of Mobile World Congress or now, MWC23, we explore the evolution of the telco business and how the industry is in many ways, mimicking transformations that took place decades ago in enterprise IT. We'll model some of the traditional enterprise vendors using ETR data and investigate how they're faring in the telecommunications sector, and we'll pose some of the key issues facing the industry this decade. First, let's take a look at what the GSMA has in store for MWC23. GSMA is the host of what used to be called Mobile World Congress. They've set the theme for this year's event as "Velocity" and they've rebranded MWC to reflect the fact that mobile technology is only one part of the story. MWC has become one of the world's premier events highlighting innovations not only in Telco, mobile and 5G, but the collision between cloud, infrastructure, apps, private networks, smart industries, machine intelligence, and AI, and more. MWC comprises an enormous ecosystem of service providers, technology companies, and firms from virtually every industry including sports and entertainment. And as well, GSMA, along with its venue partner at the Fira Barcelona, have placed a major emphasis on sustainability and public and private partnerships. Virtually every industry will be represented at the event because every industry is impacted by the trends and opportunities in this space. GSMA has said it expects 80,000 attendees at MWC this year, not quite back to 2019 levels, but trending in that direction. Of course, attendance from Chinese participants has historically been very high at the show, and obviously the continued travel issues from that region are affecting the overall attendance, but still very strong. And despite these concerns, Huawei, the giant Chinese technology company. has the largest physical presence of any exhibitor at the show. And finally, GSMA estimates that more than $300 million in economic benefit will result from the event which takes place at the end of February and early March. And The Cube will be back at MWC this year with a major presence thanks to our anchor sponsor, Dell Technologies and other supporters of our content program, including Enterprise Web, ArcaOS, VMware, Snowflake, Cisco, AWS, and others. And one of the areas we're interested in exploring is the evolution of the telco stack. It's a topic that's often talked about and one that we've observed taking place in the 1990s when the vertically integrated IBM mainframe monopoly gave way to a disintegrated and horizontal industry structure. And in many ways, the same thing is happening today in telecommunications, which is shown on the left-hand side of this diagram. Historically, telcos have relied on a hardened, integrated, and incredibly reliable, and secure set of hardware and software services that have been fully vetted and tested, and certified, and relied upon for decades. And at the top of that stack on the left are the crown jewels of the telco stack, the operational support systems and the business support systems. For the OSS, we're talking about things like network management, network operations, service delivery, quality of service, fulfillment assurance, and things like that. For the BSS systems, these refer to customer-facing elements of the stack, like revenue, order management, what products they sell, billing, and customer service. And what we're seeing is telcos have been really good at operational efficiency and making money off of transport and connectivity, but they've lacked the innovation in services and applications. They own the pipes and that works well, but others, be the over-the-top content companies, or private network providers and increasingly, cloud providers have been able to bypass the telcos, reach around them, if you will, and drive innovation. And so, the right-most diagram speaks to the need to disaggregate pieces of the stack. And while the similarities to the 1990s in enterprise IT are greater than the differences, there are things that are different. For example, the granularity of hardware infrastructure will not likely be as high where competition occurred back in the 90s at every layer of the value chain with very little infrastructure integration. That of course changed in the 2010s with converged infrastructure and hyper-converged and also software defined. So, that's one difference. And the advent of cloud, containers, microservices, and AI, none of that was really a major factor in the disintegration of legacy IT. And that probably means that disruptors can move even faster than did the likes of Intel and Microsoft, Oracle, Cisco, and the Seagates of the 1990s. As well, while many of the products and services will come from traditional enterprise IT names like Dell, HPE, Cisco, Red Hat, VMware, AWS, Microsoft, Google, et cetera, many of the names are going to be different and come from traditional network equipment providers. These are names like Ericsson and Huawei, and Nokia, and other names, like Wind River, and Rakuten, and Dish Networks. And there are enormous opportunities in data to help telecom companies and their competitors go beyond telemetry data into more advanced analytics and data monetization. There's also going to be an entirely new set of apps based on the workloads and use cases ranging from hospitals, sports arenas, race tracks, shipping ports, you name it. Virtually every vertical will participate in this transformation as the industry evolves its focus toward innovation, agility, and open ecosystems. Now remember, this is not a binary state. There are going to be greenfield companies disrupting the apple cart, but the incumbent telcos are going to have to continue to ensure newer systems work with their legacy infrastructure, in their OSS and BSS existing systems. And as we know, this is not going to be an overnight task. Integration is a difficult thing, transformations, migrations. So that's what makes this all so interesting because others can come in with Greenfield and potentially disrupt. There'll be interesting partnerships and ecosystems will form and coalitions will also form. Now, we mentioned that several traditional enterprise companies are or will be playing in this space. Now, ETR doesn't have a ton of data on specific telecom equipment and software providers, but it does have some interesting data that we cut for this breaking analysis. What we're showing here in this graphic is some of the names that we've followed over the years and how they're faring. Specifically, we did the cut within the telco sector. So the Y-axis here shows net score or spending velocity. And the horizontal axis, that shows the presence or pervasiveness in the data set. And that table insert in the upper left, that informs as to how the dots are plotted. You know, the two columns there, net score and the ends. And that red-dotted line, that horizontal line at 40%, that is an indicator of a highly elevated level. Anything above that, we consider quite outstanding. And what we'll do now is we'll comment on some of the cohorts and share with you how they're doing in telecommunications, and that sector, that vertical relative to their position overall in the data set. Let's start with the public cloud players. They're prominent in every industry. Telcos, telecommunications is no exception and it's quite an interesting cohort here. On the one hand, they can help telecommunication firms modernize and become more agile by eliminating the heavy lifting and you know, all the cloud, you know, value prop, data center costs, and the cloud benefits. At the same time, public cloud players are bringing their services to the edge, building out their own global networks and are a disruptive force to traditional telcos. All right, let's talk about Azure first. Their net score is basically identical to telco relative to its overall average. AWS's net score is higher in telco by just a few percentage points. Google Cloud platform is eight percentage points higher in telco with a 53% net score. So all three hyperscalers have an equal or stronger presence in telco than their average overall. Okay, let's look at the traditional enterprise hardware and software infrastructure cohort. Dell, Cisco, HPE, Red Hat, VMware, and Oracle. We've highlighted in this chart just as sort of indicators or proxies. Dell's net score's 10 percentage points higher in telco than its overall average. Interesting. Cisco's is a bit higher. HPE's is actually lower by about nine percentage points in the ETR survey, and VMware's is lower by about four percentage points. Now, Red Hat is really interesting. OpenStack, as we've previously reported is popular with telcos who want to build out their own private cloud. And the data shows that Red Hat OpenStack's net score is 15 percentage points higher in the telco sector than its overall average. OpenShift, on the other hand, has a net score that's four percentage points lower in telco than its overall average. So this to us talks to the pace of adoption of microservices and containers. You know, it's going to happen, but it's going to happen more slowly. Finally, Oracle's spending momentum is somewhat lower in the sector than its average, despite the firm having a decent telco business. IBM and Accenture, heavy services companies are both lower in this sector than their average. And real quickly, snowflake's net score is much lower by about 12 percentage points relative to its very high average net score of 62%. But we look for them to be a player in this space as telcos need to modernize their analytics stack and share data in a governed manner. Databricks' net score is also much lower than its average by about 13 points. And same, I would expect them to be a player as open architectures and cloud gains steam in telco. All right, let's close out now on what we're going to be talking about at MWC23 and some of the key issues that we'll be unpacking. We've talked about stack disaggregation in this breaking analysis, but the key here will be the pace at which it will reach the operational efficiency and reliability of closed stacks. Telcos, you know, in a large part, they're engineering heavy firms and much of their work takes place, kind of in the basement, in the dark. It's not really a big public hype machine, and they tend to move slowly and cautiously. While they understand the importance of agility, they're going to be careful because, you know, it's in their DNA. And so at the same time, if they don't move fast enough, they're going to get hurt and disrupted by competitors. So that's going to be a topic of conversation, and we'll be looking for proof points. And the other comment I'll make is around integration. Telcos because of their conservatism will benefit from better testing and those firms that can innovate on the testing front and have labs and certifications and innovate at that level, with an ecosystem are going to be in a better position. Because open sometimes means wild west. So the more players like Dell, HPE, Cisco, Red Hat, et cetera, that do that and align with their ecosystems and provide those resources, the faster adoption is going to go. So we'll be looking for, you know, who's actually doing that, Open RAN or Radio Access Networks. That fits in this discussion because O-RAN is an emerging network architecture. It essentially enables the use of open technologies from an ecosystem and over time, look at O-RAN is going to be open, but the questions, you know, a lot of questions remain as to when it will be able to deliver the operational efficiency of traditional RAN. Got some interesting dynamics going on. Rakuten is a company that's working hard on this problem, really focusing on operational efficiency. Then you got Dish Networks. They're also embracing O-RAN. They're coming at it more from service innovation. So that's something that we'll be monitoring and unpacking. We're going to look at cloud as a disruptor. On the one hand, cloud can help drive agility, as we said earlier and optionality, and innovation for incumbent telcos. But the flip side is going to also do the same for startups trying to disrupt and cloud attracts startups. While some of the telcos are actually embracing the cloud, many are being cautious. So that's going to be an interesting topic of discussion. And there's private wireless networks and 5G, and hyperlocal private networks, they're being deployed, you know, at the edge. This idea of open edge is also a really hot topic and this trend is going to accelerate. You know, the importance here is that the use cases are going to be widely varied. The needs of a hospital are going to be different than those of a sports venue are different from a remote drilling location, and energy or a concert venue. Things like real-time AI inference and data flows are going to bring new services and monetization opportunities. And many firms are going to be bypassing traditional telecommunications networks to build these out. Satellites as well, we're going to see, you know, in this decade, you're going to have, you're going to look down at Google Earth and you're going to see real-time. You know, today you see snapshots and so, lots of innovations going in that space. So how is this going to disrupt industries and traditional industry structures? Now, as always, we'll be looking at data angles, right? 'Cause it's in The Cube's DNA to follow the data and what opportunities and risks data brings. The Cube is going to be on location at MWC23 at the end of the month. We got a great set. We're in the walkway between halls four and five, right in Congress Square, it's booths CS60. So we'll have a full, they're called Stan CS60. We have a full schedule. I'm going to be there with Lisa Martin, Dave Nicholson and the entire Cube crew, so don't forget to stop by. All right, that's a wrap. I want to thank Alex Myerson, who's on production and manages the podcast, Ken Schiffman as well. Kristin Martin and Cheryl Knight help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at Silicon Angle, does some great stuff for us. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just search "Breaking Analysis" podcasts I publish each week on wikibon.com and silicon angle.com. And all the video content is available on demand at thecube.net. You can email me directly at david.vellante@silicon angle.com. You can DM me at dvellante or comment on my LinkedIn post. Please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for The Cube Insights powered by ETR. Thanks for watching and we'll see you at Mobile World Congress, and/or at next time on "Breaking Analysis." (bright music) (bright music fades)

(Inspiring rock music) >> Hey everyone, I'm Lisa Martin covering Data Citizens 22 brought to you by Collibra. This next conversation is going to focus on the importance of data culture. One of our Cube alumni is back; Stan Christians is Collibra's co-founder and it's Chief Data citizen. Stan, it's great to have you back on theCUBE. >> Hey Lisa, nice to be here. >> So we're going to be talking about the importance of data culture, data intelligence, maturity all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation; it also really requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >> Right. So as you know, our event is called Data Citizens because we believe that, in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations you have a lot of people, most of the employees in an organization, are somehow going to be a data citizen, right? So you need to make sure that these people are aware of it, you need to make sure that these people have the skills and competencies to do with data what is necessary, and that's on all levels, right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss we need to make this decision, that your boss is also open to and able to interpret, you know, the data presented in the dashboard to actually make that decision and take that action. Right? And once you have that "Why" to the organization that's when you have a good data culture. That's a continuous effort for most organizations because they're always moving somehow, they're hiring new people. And it has to be a continuous effort because we've seen that, on the one hand, organizations continue to be challenged with controlling their data sources and where all the data is flowing right? Which in itself creates lot of risk, but also on the other hand of the equation, you have the benefits, you know, you might look at regulatory drivers like we have to do this, right? But it's, it's much better right now to consider the competitive drivers for example. And we did an IDC study earlier this year, quite interesting, I can recommend anyone to read it, and one of the conclusions they found as they surveyed over a thousand people across organizations worldwide, is that the ones who are higher in maturity, so the organizations that really look at data as an asset, look at data as a product and actively try to be better at it don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, okay, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons. I'm doing this for regulatory reasons. You're trying to bring both of those together. And the ones that get data intelligence, right, are just going to be more successful and more competitive. That's our view and that's what we're seeing out there in the market. >> Absolutely. We know that just generally, Stan, right, The organizations that are really creating a a data culture and enabling everybody within the organization to become data citizens are, we know that, in theory, they're more competitive, they're more successful, But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >> Of course, of course it's difficult for an organization to adapt, but it's also necessary as you just said, imagine that, you know, you're a modern day organization, phones, laptops, what have you. You're not using those IT assets, right? Or you know, you're delivering them throughout the organization, but not enabling your colleagues to actually do something with that asset. Same thing is true with data today, right, if you're not properly using the data asset, and your competitors are, they're going to get more advantage. So as to how you get this done or how you establish this culture there's a few angles to look at, I would say. So one angle is obviously the leadership angle whereby whoever is the boss of data in the organization you typically have multiple bosses there, like a chief Data Officer, sometimes there's multiple, but they may have a different title, right? So I'm just going to summarize it as a data leader for a second. So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? >> Lisa: Yes. >> Now, that's one part because then you can clearly see the example of your leadership in the organization, and also the business value, and that's important because those people, their job, in essence, really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that go to right is it's not enough to just have that leadership out there but you also have to get the hearts and minds of the data champions across the organization. You really have to win them over. And if you have those two combined, and obviously good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like ePlus, then you have the pieces in place to really start upgrading that culture inch by inch, if you will. >> Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how, before we went live, we were talking about Collibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what, maybe some of the specific projects are that Collibra's data office is working on. >> Yes. And it is indeed data citizens. There are a ton of speakers here, very excited. You know, we have Barb from MIT speaking about data monetization. We have DJ Patil at the last minute on the agenda so really exciting agenda, can't wait to get back out there. But essentially you're right. So over the years at Collibra, we've been doing this now since 2008, so a good 15 years, and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around, as are we, and myself, you know, when you start a company we were four people in a garage, if you will, so everybody's wearing all sorts of hat at that time. But over the years I've run pre-sales at Collibra, I've run post sales, partnerships, product, et cetera, and as our company got a little bit biggish, we're now 1,200 something like that, people in the company I believe, systems and processes become a lot more important, right? So we said, you know, Collibra isn't the size of our customers yet, but we're getting there in terms of organization, structure, process systems et cetera. So we said it's really time for us to put our money where our mouth is, and to set up our own data office, which is what we were seeing that all of our customers are doing, and which is what we're seeing that organizations worldwide are doing and Gartner was predicting as well. They said, okay, organizations have an HR unit, they have a finance unit, and over time they'll all have a department, if you will, that is responsible somehow for the data. >> Lisa: Hm. >> So we said, okay, let's try to set an example with Collibra. Let's set up our own data office in such a way that other people can take away with it, right? Can take away from it? So we set up a data strategy, we started building data products, took care of the data infrastructure, that sort of good stuff, And in doing all of that, Lisa, exactly as you said, we said, okay, we need to also use our own products and our own practices, right? And from that use, learn how we can make the product better, learn how we can make the practice better and share that learning with all of the markets, of course. And on Monday mornings, we sometimes refer to that as eating our own dog foods, Friday evenings, we refer to that as drinking our own champagne. >> Lisa: I like it. >> So we, we had a (both chuckle) We had the drive do this, you know, there's a clear business reason, so we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should follow. This is just the organization that works at our company, but it can serve as an inspiration. So we have pillars, which is data science, The data product builders, if you will or the people who help the business build data products, we have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products, can run, the data can flow and, you know, the quality can be checked. And then we have a data intelligence or data governance pillar where we have those data governance data intelligence stakeholders who help the business as a sort of data partners to the business stakeholders. So that's how we've organized it. And then we started following the Collibra approach, which is, well, what are the challenges that our business stakeholders have in HR, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a roadmap, and started execution on use case after use case. And a few important ones there are very simple, we see them with all our customers as well, people love talking about the catalog, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in Deagle and privacy, So they have their process registry, and they can see how the data flows. So that's a popular starting place and that turns into a marketplace so that if new analysts and data citizens join Collibra, they immediately have a place to go to to look at what data is out there for me as an analyst or data scientist or whatever, to do my job, right? So they can immediately get access to the data. And another one that we did is around trusted business reporting. We're seeing that, since 2008, you know, self-service BI allowed everyone to make beautiful dashboards, you know, by pie charts. I always, my pet peeve is the pie charts because I love pie, and you shouldn't always be using pie charts, but essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report? They're reporting on the same thing but the numbers seem different, right? So that's why we have trusted business reporting. So we know if the reports, the dashboard, a data product essentially, is built, we know that all the right steps are being followed, and that whoever is consuming that can be quite confident in the result. >> Lisa: Right, and that confidence is absolutely key. >> Exactly. Yes. >> Absolutely. Talk a little bit about some of the the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >> KPIs and measuring is a big topic in the chief data officer profession I would say, and again, it always varies, with respect to your organization, but there's a few that we use that might be of interest to you. So remember you have those three pillars, right? And we have metrics across those pillars. So, for example, a pillar on the data engineering side is going to be more related to that uptime, right? Is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data signs and the products. Are people using them? Are they getting value from it? Can we calculate that value in a monetary perspective, right? >> Lisa: Yes. >> So that we can, to the rest of the business, continue to say, "We're tracking all those numbers and those numbers indicate that value is generated" and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example you have a number of domains in a data mesh [Indistinct] People talk about being the owner a data domain for example, like product or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open? Closed? How many data products are built according to process? And so on and so forth, so these are a set of examples of KPI's. There's a lot more but hopefully those can already inspire the audience. >> Absolutely. So we've, we've talked about the rise of cheap data offices, it's only accelerating. You mentioned this is like a 10-year journey. So if you were to look into a crystal ball, what do you see, in terms of the maturation of data offices over the next decade? >> So we, we've seen, indeed, the role sort of grow up. I think in 2010 there may have been like, 10 chief data officers or something, Gartner has exact numbers on them. But then they grew, you know, 400's they were like mostly in financial services, but they expanded them to all industries and the number is estimated to be about 20,000 right now. >> Wow. >> And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy, support for the digital program and now all about data products, right? So as a data leader, you now need all those competences and need to include them in your strategy. How is that going to evolve for the next couple of years? I wish I had one of those crystal balls, right? But essentially, I think for the next couple of years there's going to be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data officers. So you'll see, over the years that's going to evolve more digital and more data products. So for the next three, five years, my prediction is it's all going to be about data products because it's an immediate link between the data and the dollar essentially. >> Right. >> So that's going to be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up a few years. I think there's going to be a continued challenge for the chief data officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done, will be the ones that are successful, and the ones who get that done will be the ones that do it on the basis of data monetization, right? Connecting value to the data and making that very clear to all the data citizens in the organization, right? >> Right, really creating that value chain. >> In that sense they'll need to have both, you know, technical audiences and non-technical audiences aligned of course, and they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you are waking up data citizens across the organization and you make everyone in the organization think about data as an essence. >> Absolutely, because there's so much value that can be extracted if organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely going to keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show, that you mentioned in that IDC study you mentioned Gartner as well. Organizations have so much more likelihood of being successful and being competitive. So we're going to watch this space. Stan, thank you so much for joining me on theCUBE at Data Citizens 22. We appreciate it. >> Thanks for having me over. >> From Data Citizens 22, I'm Lisa Martin you're watching theCUBE, the leader in live tech coverage. (inspiring rock music) >> Okay, this concludes our coverage of Data Citizens 2022 brought to you by Collibra. Remember, all these videos are available on demand at theCUBE.net. And don't forget to check out siliconangle.com for all the news and wikibon.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR, Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to Collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on theCUBE Your leader in enterprise and emerging tech coverage. We'll see you soon. (inspiring rock music continues)

(upbeat techno music) >> Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions, and they were largely confined to regulated industries that had to comply with public policy mandates. But as the cloud went mainstream the tech giants showed us how valuable data could become, and the value proposition for data quality and trust, it evolved from primarily a compliance driven issue, to becoming a linchpin of competitive advantage. But, data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper-specialized skills, to develop data architectures and processes, to serve the myriad data needs of organizations. And it resulted in a lot of frustration, with data initiatives for most organizations, that didn't have the resources of the cloud guys and the social media giants, to really attack their data problems and turn data into gold. This is why today, for example, there's quite a bit of momentum to re-thinking monolithic data architectures. You see, you hear about initiatives like Data Mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business users. You hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver, like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that but also, how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. In other words, while it's enticing to experiment, and run fast and loose with data initiatives, kind of like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated and intelligent. Governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is going to use data that is entrusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. Hello and welcome to theCUBE's coverage of Data Citizens made possible by Collibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Vellante and I'm one of the hosts of our program which is running in parallel to Data Citizens. Now at theCUBE we like to say we extract the signal from the noise, and over the next couple of days we're going to feature some of the themes from the keynote speakers at Data Citizens, and we'll hear from several of the executives. Felix Van de Maele, who is the co-founder and CEO of Collibra, will join us. Along with one of the other founders of Collibra, Stan Christiaens, who's going to join my colleague Lisa Martin. I'm going to also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Haslbeck. He's the Vice President of Data Quality at Collibra. He's an amazingly smart dude who founded Owl DQ, a company that he sold to Collibra last year. Now, many companies they didn't make it through the Hadoop era, you know they missed the industry waves and they became driftwood. Collibra, on the other hand, has evolved its business, they've leveraged the cloud, expanded its product portfolio and leaned in heavily to some major partnerships with cloud providers as well as receiving a strategic investment from Snowflake, earlier this year. So, it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. (upbeat rock music) Last year theCUBE covered Data Citizens, Collibra's customer event, and the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know starting with the Hadoop movement, we had Data lakes, we had Spark, the ascendancy of programming languages like Python, the introduction of frameworks like Tensorflow, the rise of AI, Low Code, No Code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives, and we said at the time, you know maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation. Meaning, making it easier for domain experts to both gain insights from data, trust the data, and begin to use that data in new ways, fueling data products, monetization, and insights. Data Citizens 2022 is back and we're pleased to have Felix Van de Maele who is the founder and CEO of Collibra. He's on theCUBE. We're excited to have you Felix. Good to see you again. >> Likewise Dave. Thanks for having me again. >> You bet. All right, we're going to get the update from Felix on the current data landscape, how he sees it why data intelligence is more important now than ever, and get current on what Collibra has been up to over the past year, and what's changed since Data citizens 2021, and we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends and we're not just snapping back to the 2010s, that's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s, from the previous decade, and what challenges does that bring for your customers? >> Yeah, absolutely, and and I think you said it well, Dave and the intro that, that rising complexity and fragmentation, in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use, has only gotten more more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under, respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well. Which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity, and fragmentation. So, it's become much more acute. And to your earlier point, we do live in a different world and and the past couple of years we could probably just kind of brute force it, right? We could focus on, on the top line, there was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, how do we truly get the value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale with data, not just from a a technology and infrastructure perspective, but how do we actually scale data from an organizational perspective, right? You said at the, the people and process, how do we do that at scale? And that's only, only, only becoming much more important, and we do believe that the, the economic environment that we find ourselves in today is going to be catalyst for organizations to really take that more seriously if, if, if you will, than they maybe have in the have in the past. >> You know, I don't know when you guys founded Collibra, if you had a sense as to how complicated it was going to get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >> Yeah, absolutely. We, we started Collibra in 2008. So, in some sense and the, the last kind of financial crisis and that was really the, the start of Collibra, where we found product market fit, working with large financial institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis. And kind of here we are again, in a very different environment of course 15 years, almost 15 years later, but data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So, what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it Data Citizens, we truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we still relatively early in that, in that journey. >> Well that's interesting, because you know, in my observation it takes 7 to 10 years to actually build a company, and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your current momentum? >> Yeah, absolutely. Again, there's a lot of tailwind organizations that are only maturing their data practices and we've seen that kind of transform or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world with its Adobe, Heineken, Bank of America and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in the, in the market with some of the cloud partners like Google, Amazon, Snowflake, Data Breaks, and and others, right? As those kind of new modern data infrastructures, modern data architectures, are definitely all moving to the cloud. A great opportunity for us, our partners, and of course our customers, to help them kind of transition to the cloud even faster. And so we see a lot of excitement and momentum there. We did an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course data quality isn't new but I think there's a lot of reasons why we're so excited about quality and observability now. One, is around leveraging AI machine learning again to drive more automation. And a second is that those data pipelines, that are now being created in the cloud, in these modern data architecture, architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously, has become absolutely critical so that they're really excited about, about that as well. And on the organizational side, I'm sure you've heard the term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believed in. Federated, focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations, and so that aligns really well with our vision and from a product perspective, we've seen a lot of momentum with our customers there as well. >> Yeah, you know, a couple things there. I mean, the acquisition of OwlDQ, you know Kirk Haslbeck and, and their team. It's interesting, you know the whole data quality used to be this back office function and and really confined to highly regulated industries. It's come to the front office, it's top of mind for Chief Data Officers. Data mesh, you mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So, let's chat a little bit about the, the products. We're going to go deeper into products later on, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the the under the covers in security, sort of making data more accessible for people, just dealing with workflows and processes, as you talked about earlier. Tell us a little bit about what you're introducing. >> Yeah, absolutely. We we're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission. Either customers are still start, are just starting on that, on that journey. We want to make it as easy as possible for the, for organization to actually get started, because we know that's important that they do. And for our organization and customers, that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again to make it easier for, really to, to accomplish that mission and vision around that Data Citizen, that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving, a lot of kind of ease of adoption, ease of use, but also then, how do we make sure that, as clear becomes this kind of mission critical enterprise platform, from a security performance, architecture scale supportability, that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme. From an innovation perspective, from a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One, is around data marketplace. Again, a lot of our customers have plans in that direction, How to make it easy? How do we make How do we make available to true kind of shopping experience? So that anybody in the organization can, in a very easy search first way, find the right data product, find the right dataset, that they can then consume. Usage analytics, how do you, how do we help organizations drive adoption? Tell them where they're working really well and where they have opportunities. Homepages again to, to make things easy for, for people, for anyone in your organization, to kind of get started with Collibra. You mentioned Workflow Designer, again, we have a very powerful enterprise platform, one of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a, a new Low-Code, No-Code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around Collibra protect, which in partnership with Snowflake, which has been a strategic investor in Collibra, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PIA data, is managed as a much more effective, effective rate. Really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily, and quickly, and widely as we can? Moving that to the cloud has been a big part of our strategy. So, we launch our data quality cloud product, as well as making use of those, those native compute capabilities and platforms, like Snowflake, Databricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down, so we're actually pushing down the computer and data quality, to monitoring into the underlying platform, which again from a scale performance and ease of use perspective, is going to make a massive difference. And then more broadly, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical, and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So that's a lot coming out, the team has been work, at work really hard, and we are really really excited about what we are coming, what we're bringing to market. >> Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you you talked about, you know, the marketplace, you know you think about Data Mesh, you think of data as product, one of the key principles, you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been, been so hard. So, how do you see sort of the future and, you know give us the, your closing thoughts please? >> Yeah, absolutely. And, and I think we we're really at a pivotal moment and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not going to fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to, deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can, as kind of our, as our mission. And so I'm really, really excited to see what we, what we are going to, how the marks are going to evolve over the next, next few quarters and years. I think the trend is clearly there. We talked about Data Mesh, this kind of federated approach focus on data products, is just another signal that we believe, that a lot of our organization are now at the time, they're understanding need to go beyond just the technology. I really, really think about how to actually scale data as a business function, just like we've done with IT, with HR, with sales and marketing, with finance. That's how we need to think about data. I think now is the time, given the economic environment that we are in, much more focus on control, much more focus on productivity, efficiency, and now is the time we need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >> Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much. Good luck in, in San Diego. I know you're going to crush it out there. >> Thank you Dave. >> Yeah, it's a great spot for an in-person event and and of course the content post-event is going to be available at collibra.com and you can of course catch theCUBE coverage at theCUBE.net and all the news at siliconangle.com. This is Dave Vellante for theCUBE, your leader in enterprise and emerging tech coverage. (upbeat techno music)

>>Collibra is a company that was founded in 2008 right before the so-called modern big data era kicked into high gear. The company was one of the first to focus its business on data governance. Now, historically, data governance and data quality initiatives, they were back office functions and they were largely confined to regulatory regulated industries that had to comply with public policy mandates. But as the cloud went mainstream, the tech giants showed us how valuable data could become and the value proposition for data quality and trust. It evolved from primarily a compliance driven issue to becoming a lynchpin of competitive advantage. But data in the decade of the 2010s was largely about getting the technology to work. You had these highly centralized technical teams that were formed and they had hyper specialized skills to develop data architectures and processes to serve the myriad data needs of organizations. >>And it resulted in a lot of frustration with data initiatives for most organizations that didn't have the resources of the cloud guys and the social media giants to really attack their data problems and turn data into gold. This is why today for example, this quite a bit of momentum to rethinking monolithic data architectures. You see, you hear about initiatives like data mesh and the idea of data as a product. They're gaining traction as a way to better serve the the data needs of decentralized business Uni users, you hear a lot about data democratization. So these decentralization efforts around data, they're great, but they create a new set of problems. Specifically, how do you deliver like a self-service infrastructure to business users and domain experts? Now the cloud is definitely helping with that, but also how do you automate governance? This becomes especially tricky as protecting data privacy has become more and more important. >>In other words, while it's enticing to experiment and run fast and loose with data initiatives kinda like the Wild West, to find new veins of gold, it has to be done responsibly. As such, the idea of data governance has had to evolve to become more automated. And intelligence governance and data lineage is still fundamental to ensuring trust as data. It moves like water through an organization. No one is gonna use data that isn't trusted. Metadata has become increasingly important for data discovery and data classification. As data flows through an organization, the continuously ability to check for data flaws and automating that data quality, they become a functional requirement of any modern data management platform. And finally, data privacy has become a critical adjacency to cyber security. So you can see how data governance has evolved into a much richer set of capabilities than it was 10 or 15 years ago. >>Hello and welcome to the Cube's coverage of Data Citizens made possible by Calibra, a leader in so-called Data intelligence and the host of Data Citizens 2022, which is taking place in San Diego. My name is Dave Ante and I'm one of the hosts of our program, which is running in parallel to data citizens. Now at the Cube we like to say we extract the signal from the noise, and over the, the next couple of days, we're gonna feature some of the themes from the keynote speakers at Data Citizens and we'll hear from several of the executives. Felix Von Dala, who is the co-founder and CEO of Collibra, will join us along with one of the other founders of Collibra, Stan Christians, who's gonna join my colleague Lisa Martin. I'm gonna also sit down with Laura Sellers, she's the Chief Product Officer at Collibra. We'll talk about some of the, the announcements and innovations they're making at the event, and then we'll dig in further to data quality with Kirk Hasselbeck. >>He's the vice president of Data quality at Collibra. He's an amazingly smart dude who founded Owl dq, a company that he sold to Col to Collibra last year. Now many companies, they didn't make it through the Hado era, you know, they missed the industry waves and they became Driftwood. Collibra, on the other hand, has evolved its business. They've leveraged the cloud, expanded its product portfolio, and leaned in heavily to some major partnerships with cloud providers, as well as receiving a strategic investment from Snowflake earlier this year. So it's a really interesting story that we're thrilled to be sharing with you. Thanks for watching and I hope you enjoy the program. >>Last year, the Cube Covered Data Citizens Collibra's customer event. And the premise that we put forth prior to that event was that despite all the innovation that's gone on over the last decade or more with data, you know, starting with the Hado movement, we had data lakes, we'd spark the ascendancy of programming languages like Python, the introduction of frameworks like TensorFlow, the rise of ai, low code, no code, et cetera. Businesses still find it's too difficult to get more value from their data initiatives. And we said at the time, you know, maybe it's time to rethink data innovation. While a lot of the effort has been focused on, you know, more efficiently storing and processing data, perhaps more energy needs to go into thinking about the people and the process side of the equation, meaning making it easier for domain experts to both gain insights for data, trust the data, and begin to use that data in new ways, fueling data, products, monetization and insights data citizens 2022 is back and we're pleased to have Felix Van Dema, who is the founder and CEO of Collibra. He's on the cube or excited to have you, Felix. Good to see you again. >>Likewise Dave. Thanks for having me again. >>You bet. All right, we're gonna get the update from Felix on the current data landscape, how he sees it, why data intelligence is more important now than ever and get current on what Collibra has been up to over the past year and what's changed since Data Citizens 2021. And we may even touch on some of the product news. So Felix, we're living in a very different world today with businesses and consumers. They're struggling with things like supply chains, uncertain economic trends, and we're not just snapping back to the 2010s. That's clear, and that's really true as well in the world of data. So what's different in your mind, in the data landscape of the 2020s from the previous decade, and what challenges does that bring for your customers? >>Yeah, absolutely. And, and I think you said it well, Dave, and and the intro that that rising complexity and fragmentation in the broader data landscape, that hasn't gotten any better over the last couple of years. When when we talk to our customers, that level of fragmentation, the complexity, how do we find data that we can trust, that we know we can use has only gotten kinda more, more difficult. So that trend that's continuing, I think what is changing is that trend has become much more acute. Well, the other thing we've seen over the last couple of years is that the level of scrutiny that organizations are under respect to data, as data becomes more mission critical, as data becomes more impactful than important, the level of scrutiny with respect to privacy, security, regulatory compliance, as only increasing as well, which again, is really difficult in this environment of continuous innovation, continuous change, continuous growing complexity and fragmentation. >>So it's become much more acute. And, and to your earlier point, we do live in a different world and and the the past couple of years we could probably just kind of brute for it, right? We could focus on, on the top line. There was enough kind of investments to be, to be had. I think nowadays organizations are focused or are, are, are, are, are, are in a very different environment where there's much more focus on cost control, productivity, efficiency, How do we truly get value from that data? So again, I think it just another incentive for organization to now truly look at data and to scale it data, not just from a a technology and infrastructure perspective, but how do you actually scale data from an organizational perspective, right? You said at the the people and process, how do we do that at scale? And that's only, only only becoming much more important. And we do believe that the, the economic environment that we find ourselves in today is gonna be catalyst for organizations to really dig out more seriously if, if, if, if you will, than they maybe have in the have in the best. >>You know, I don't know when you guys founded Collibra, if, if you had a sense as to how complicated it was gonna get, but you've been on a mission to really address these problems from the beginning. How would you describe your, your, your mission and what are you doing to address these challenges? >>Yeah, absolutely. We, we started Colli in 2008. So in some sense and the, the last kind of financial crisis, and that was really the, the start of Colli where we found product market fit, working with large finance institutions to help them cope with the increasing compliance requirements that they were faced with because of the, of the financial crisis and kind of here we are again in a very different environment, of course 15 years, almost 15 years later. But data only becoming more important. But our mission to deliver trusted data for every user, every use case and across every source, frankly, has only become more important. So what has been an incredible journey over the last 14, 15 years, I think we're still relatively early in our mission to again, be able to provide everyone, and that's why we call it data citizens. We truly believe that everyone in the organization should be able to use trusted data in an easy, easy matter. That mission is is only becoming more important, more relevant. We definitely have a lot more work ahead of us because we are still relatively early in that, in that journey. >>Well, that's interesting because, you know, in my observation it takes seven to 10 years to actually build a company and then the fact that you're still in the early days is kind of interesting. I mean, you, Collibra's had a good 12 months or so since we last spoke at Data Citizens. Give us the latest update on your business. What do people need to know about your, your current momentum? >>Yeah, absolutely. Again, there's, there's a lot of tail organizations that are only maturing the data practices and we've seen it kind of transform or, or, or influence a lot of our business growth that we've seen, broader adoption of the platform. We work at some of the largest organizations in the world where it's Adobe, Heineken, Bank of America, and many more. We have now over 600 enterprise customers, all industry leaders and every single vertical. So it's, it's really exciting to see that and continue to partner with those organizations. On the partnership side, again, a lot of momentum in the org in, in the, in the markets with some of the cloud partners like Google, Amazon, Snowflake, data bricks and, and others, right? As those kind of new modern data infrastructures, modern data architectures that are definitely all moving to the cloud, a great opportunity for us, our partners and of course our customers to help them kind of transition to the cloud even faster. >>And so we see a lot of excitement and momentum there within an acquisition about 18 months ago around data quality, data observability, which we believe is an enormous opportunity. Of course, data quality isn't new, but I think there's a lot of reasons why we're so excited about quality and observability now. One is around leveraging ai, machine learning, again to drive more automation. And the second is that those data pipelines that are now being created in the cloud, in these modern data architecture arch architectures, they've become mission critical. They've become real time. And so monitoring, observing those data pipelines continuously has become absolutely critical so that they're really excited about about that as well. And on the organizational side, I'm sure you've heard a term around kind of data mesh, something that's gaining a lot of momentum, rightfully so. It's really the type of governance that we always believe. Then federated focused on domains, giving a lot of ownership to different teams. I think that's the way to scale data organizations. And so that aligns really well with our vision and, and from a product perspective, we've seen a lot of momentum with our customers there as well. >>Yeah, you know, a couple things there. I mean, the acquisition of i l dq, you know, Kirk Hasselbeck and, and their team, it's interesting, you know, the whole data quality used to be this back office function and, and really confined to highly regulated industries. It's come to the front office, it's top of mind for chief data officers, data mesh. You mentioned you guys are a connective tissue for all these different nodes on the data mesh. That's key. And of course we see you at all the shows. You're, you're a critical part of many ecosystems and you're developing your own ecosystem. So let's chat a little bit about the, the products. We're gonna go deeper in into products later on at, at Data Citizens 22, but we know you're debuting some, some new innovations, you know, whether it's, you know, the, the the under the covers in security, sort of making data more accessible for people just dealing with workflows and processes as you talked about earlier. Tell us a little bit about what you're introducing. >>Yeah, absolutely. We're super excited, a ton of innovation. And if we think about the big theme and like, like I said, we're still relatively early in this, in this journey towards kind of that mission of data intelligence that really bolts and compelling mission, either customers are still start, are just starting on that, on that journey. We wanna make it as easy as possible for the, for our organization to actually get started because we know that's important that they do. And for our organization and customers that have been with us for some time, there's still a tremendous amount of opportunity to kind of expand the platform further. And again, to make it easier for really to, to accomplish that mission and vision around that data citizen that everyone has access to trustworthy data in a very easy, easy way. So that's really the theme of a lot of the innovation that we're driving. >>A lot of kind of ease of adoption, ease of use, but also then how do we make sure that lio becomes this kind of mission critical enterprise platform from a security performance architecture scale supportability that we're truly able to deliver that kind of an enterprise mission critical platform. And so that's the big theme from an innovation perspective, From a product perspective, a lot of new innovation that we're really excited about. A couple of highlights. One is around data marketplace. Again, a lot of our customers have plans in that direction, how to make it easy. How do we make, how do we make available to true kind of shopping experience that anybody in your organization can, in a very easy search first way, find the right data product, find the right dataset, that data can then consume usage analytics. How do you, how do we help organizations drive adoption, tell them where they're working really well and where they have opportunities homepages again to, to make things easy for, for people, for anyone in your organization to kind of get started with ppia, you mentioned workflow designer, again, we have a very powerful enterprise platform. >>One of our key differentiators is the ability to really drive a lot of automation through workflows. And now we provided a new low code, no code kind of workflow designer experience. So, so really customers can take it to the next level. There's a lot more new product around K Bear Protect, which in partnership with Snowflake, which has been a strategic investor in kib, focused on how do we make access governance easier? How do we, how do we, how are we able to make sure that as you move to the cloud, things like access management, masking around sensitive data, PII data is managed as much more effective, effective rate, really excited about that product. There's more around data quality. Again, how do we, how do we get that deployed as easily and quickly and widely as we can? Moving that to the cloud has been a big part of our strategy. >>So we launch more data quality cloud product as well as making use of those, those native compute capabilities in platforms like Snowflake, Data, Bricks, Google, Amazon, and others. And so we are bettering a capability, a capability that we call push down. So actually pushing down the computer and data quality, the monitoring into the underlying platform, which again, from a scale performance and ease of use perspective is gonna make a massive difference. And then more broadly, we, we talked a little bit about the ecosystem. Again, integrations, we talk about being able to connect to every source. Integrations are absolutely critical and we're really excited to deliver new integrations with Snowflake, Azure and Google Cloud storage as well. So there's a lot coming out. The, the team has been work at work really hard and we are really, really excited about what we are coming, what we're bringing to markets. >>Yeah, a lot going on there. I wonder if you could give us your, your closing thoughts. I mean, you, you talked about, you know, the marketplace, you know, you think about data mesh, you think of data as product, one of the key principles you think about monetization. This is really different than what we've been used to in data, which is just getting the technology to work has been been so hard. So how do you see sort of the future and, you know, give us the, your closing thoughts please? >>Yeah, absolutely. And I, and I think we we're really at this pivotal moment, and I think you said it well. We, we all know the constraint and the challenges with data, how to actually do data at scale. And while we've seen a ton of innovation on the infrastructure side, we fundamentally believe that just getting a faster database is important, but it's not gonna fully solve the challenges and truly kind of deliver on the opportunity. And that's why now is really the time to deliver this data intelligence vision, this data intelligence platform. We are still early, making it as easy as we can. It's kind of, of our, it's our mission. And so I'm really, really excited to see what we, what we are gonna, how the marks gonna evolve over the next, next few quarters and years. I think the trend is clearly there when we talk about data mesh, this kind of federated approach folks on data products is just another signal that we believe that a lot of our organization are now at the time. >>The understanding need to go beyond just the technology. I really, really think about how do we actually scale data as a business function, just like we've done with it, with, with hr, with, with sales and marketing, with finance. That's how we need to think about data. I think now is the time given the economic environment that we are in much more focus on control, much more focused on productivity efficiency and now's the time. We need to look beyond just the technology and infrastructure to think of how to scale data, how to manage data at scale. >>Yeah, it's a new era. The next 10 years of data won't be like the last, as I always say. Felix, thanks so much and good luck in, in San Diego. I know you're gonna crush it out there. >>Thank you Dave. >>Yeah, it's a great spot for an in-person event and, and of course the content post event is gonna be available@collibra.com and you can of course catch the cube coverage@thecube.net and all the news@siliconangle.com. This is Dave Valante for the cube, your leader in enterprise and emerging tech coverage. >>Hi, I'm Jay from Collibra's Data Office. Today I want to talk to you about Collibra's data intelligence cloud. We often say Collibra is a single system of engagement for all of your data. Now, when I say data, I mean data in the broadest sense of the word, including reference and metadata. Think of metrics, reports, APIs, systems, policies, and even business processes that produce or consume data. Now, the beauty of this platform is that it ensures all of your users have an easy way to find, understand, trust, and access data. But how do you get started? Well, here are seven steps to help you get going. One, start with the data. What's data intelligence? Without data leverage the Collibra data catalog to automatically profile and classify your enterprise data wherever that data lives, databases, data lakes or data warehouses, whether on the cloud or on premise. >>Two, you'll then wanna organize the data and you'll do that with data communities. This can be by department, find a business or functional team, however your organization organizes work and accountability. And for that you'll establish community owners, communities, make it easy for people to navigate through the platform, find the data and will help create a sense of belonging for users. An important and related side note here, we find it's typical in many organizations that data is thought of is just an asset and IT and data offices are viewed as the owners of it and who are really the central teams performing analytics as a service provider to the enterprise. We believe data is more than an asset, it's a true product that can be converted to value. And that also means establishing business ownership of data where that strategy and ROI come together with subject matter expertise. >>Okay, three. Next, back to those communities there, the data owners should explain and define their data, not just the tables and columns, but also the related business terms, metrics and KPIs. These objects we call these assets are typically organized into business glossaries and data dictionaries. I definitely recommend starting with the topics that are most important to the business. Four, those steps that enable you and your users to have some fun with it. Linking everything together builds your knowledge graph and also known as a metadata graph by linking or relating these assets together. For example, a data set to a KPI to a report now enables your users to see what we call the lineage diagram that visualizes where the data in your dashboards actually came from and what the data means and who's responsible for it. Speaking of which, here's five. Leverage the calibra trusted business reporting solution on the marketplace, which comes with workflows for those owners to certify their reports, KPIs, and data sets. >>This helps them force their trust in their data. Six, easy to navigate dashboards or landing pages right in your platform for your company's business processes are the most effective way for everyone to better understand and take action on data. Here's a pro tip, use the dashboard design kit on the marketplace to help you build compelling dashboards. Finally, seven, promote the value of this to your users and be sure to schedule enablement office hours and new employee onboarding sessions to get folks excited about what you've built and implemented. Better yet, invite all of those community and data owners to these sessions so that they can show off the value that they've created. Those are my seven tips to get going with Collibra. I hope these have been useful. For more information, be sure to visit collibra.com. >>Welcome to the Cube's coverage of Data Citizens 2022 Collibra's customer event. My name is Dave Valante. With us is Kirk Hasselbeck, who's the vice president of Data Quality of Collibra Kirk, good to see you. Welcome. >>Thanks for having me, Dave. Excited to be here. >>You bet. Okay, we're gonna discuss data quality observability. It's a hot trend right now. You founded a data quality company, OWL dq, and it was acquired by Collibra last year. Congratulations. And now you lead data quality at Collibra. So we're hearing a lot about data quality right now. Why is it such a priority? Take us through your thoughts on that. >>Yeah, absolutely. It's, it's definitely exciting times for data quality, which you're right, has been around for a long time. So why now and why is it so much more exciting than it used to be? I think it's a bit stale, but we all know that companies use more data than ever before and the variety has changed and the volume has grown. And, and while I think that remains true, there are a couple other hidden factors at play that everyone's so interested in as, as to why this is becoming so important now. And, and I guess you could kind of break this down simply and think about if Dave, you and I were gonna build, you know, a new healthcare application and monitor the heartbeat of individuals, imagine if we get that wrong, you know, what the ramifications could be, what, what those incidents would look like, or maybe better yet, we try to build a, a new trading algorithm with a crossover strategy where the 50 day crosses the, the 10 day average. >>And imagine if the data underlying the inputs to that is incorrect. We will probably have major financial ramifications in that sense. So, you know, it kind of starts there where everybody's realizing that we're all data companies and if we are using bad data, we're likely making incorrect business decisions. But I think there's kind of two other things at play. You know, I, I bought a car not too long ago and my dad called and said, How many cylinders does it have? And I realized in that moment, you know, I might have failed him because, cause I didn't know. And, and I used to ask those types of questions about any lock brakes and cylinders and, and you know, if it's manual or, or automatic and, and I realized I now just buy a car that I hope works. And it's so complicated with all the computer chips, I, I really don't know that much about it. >>And, and that's what's happening with data. We're just loading so much of it. And it's so complex that the way companies consume them in the IT function is that they bring in a lot of data and then they syndicate it out to the business. And it turns out that the, the individuals loading and consuming all of this data for the company actually may not know that much about the data itself, and that's not even their job anymore. So we'll talk more about that in a minute, but that's really what's setting the foreground for this observability play and why everybody's so interested. It, it's because we're becoming less close to the intricacies of the data and we just expect it to always be there and be correct. >>You know, the other thing too about data quality, and for years we did the MIT CDO IQ event, we didn't do it last year, Covid messed everything up. But the observation I would make there thoughts is, is it data quality? Used to be information quality used to be this back office function, and then it became sort of front office with financial services and government and healthcare, these highly regulated industries. And then the whole chief data officer thing happened and people were realizing, well, they sort of flipped the bit from sort of a data as a, a risk to data as a, as an asset. And now as we say, we're gonna talk about observability. And so it's really become front and center just the whole quality issue because data's so fundamental, hasn't it? >>Yeah, absolutely. I mean, let's imagine we pull up our phones right now and I go to my, my favorite stock ticker app and I check out the NASDAQ market cap. I really have no idea if that's the correct number. I know it's a number, it looks large, it's in a numeric field. And, and that's kind of what's going on. There's, there's so many numbers and they're coming from all of these different sources and data providers and they're getting consumed and passed along. But there isn't really a way to tactically put controls on every number and metric across every field we plan to monitor, but with the scale that we've achieved in early days, even before calibra. And what's been so exciting is we have these types of observation techniques, these data monitors that can actually track past performance of every field at scale. And why that's so interesting and why I think the CDO is, is listening right intently nowadays to this topic is, so maybe we could surface all of these problems with the right solution of data observability and with the right scale and then just be alerted on breaking trends. So we're sort of shifting away from this world of must write a condition and then when that condition breaks, that was always known as a break record. But what about breaking trends and root cause analysis? And is it possible to do that, you know, with less human intervention? And so I think most people are seeing now that it's going to have to be a software tool and a computer system. It's, it's not ever going to be based on one or two domain experts anymore. >>So, So how does data observability relate to data quality? Are they sort of two sides of the same coin? Are they, are they cousins? What's your perspective on that? >>Yeah, it's, it's super interesting. It's an emerging market. So the language is changing a lot of the topic and areas changing the way that I like to say it or break it down because the, the lingo is constantly moving is, you know, as a target on this space is really breaking records versus breaking trends. And I could write a condition when this thing happens, it's wrong and when it doesn't it's correct. Or I could look for a trend and I'll give you a good example. You know, everybody's talking about fresh data and stale data and, and why would that matter? Well, if your data never arrived or only part of it arrived or didn't arrive on time, it's likely stale and there will not be a condition that you could write that would show you all the good in the bads. That was kind of your, your traditional approach of data quality break records. But your modern day approach is you lost a significant portion of your data, or it did not arrive on time to make that decision accurately on time. And that's a hidden concern. Some people call this freshness, we call it stale data, but it all points to the same idea of the thing that you're observing may not be a data quality condition anymore. It may be a breakdown in the data pipeline. And with thousands of data pipelines in play for every company out there there, there's more than a couple of these happening every day. >>So what's the Collibra angle on all this stuff made the acquisition, you got data quality observability coming together, you guys have a lot of expertise in, in this area, but you hear providence of data, you just talked about, you know, stale data, you know, the, the whole trend toward real time. How is Calibra approaching the problem and what's unique about your approach? >>Well, I think where we're fortunate is with our background, myself and team, we sort of lived this problem for a long time, you know, in, in the Wall Street days about a decade ago. And we saw it from many different angles. And what we came up with before it was called data observability or reliability was basically the, the underpinnings of that. So we're a little bit ahead of the curve there when most people evaluate our solution, it's more advanced than some of the observation techniques that that currently exist. But we've also always covered data quality and we believe that people want to know more, they need more insights, and they want to see break records and breaking trends together so they can correlate the root cause. And we hear that all the time. I have so many things going wrong, just show me the big picture, help me find the thing that if I were to fix it today would make the most impact. So we're really focused on root cause analysis, business impact, connecting it with lineage and catalog metadata. And as that grows, you can actually achieve total data governance at this point with the acquisition of what was a Lineage company years ago, and then my company Ldq now Collibra, Data quality Collibra may be the best positioned for total data governance and intelligence in the space. >>Well, you mentioned financial services a couple of times and some examples, remember the flash crash in 2010. Nobody had any idea what that was, you know, they just said, Oh, it's a glitch, you know, so they didn't understand the root cause of it. So this is a really interesting topic to me. So we know at Data Citizens 22 that you're announcing, you gotta announce new products, right? You're yearly event what's, what's new. Give us a sense as to what products are coming out, but specifically around data quality and observability. >>Absolutely. There's this, you know, there's always a next thing on the forefront. And the one right now is these hyperscalers in the cloud. So you have databases like Snowflake and Big Query and Data Bricks is Delta Lake and SQL Pushdown. And ultimately what that means is a lot of people are storing in loading data even faster in a SaaS like model. And we've started to hook in to these databases. And while we've always worked with the the same databases in the past, they're supported today we're doing something called Native Database pushdown, where the entire compute and data activity happens in the database. And why that is so interesting and powerful now is everyone's concerned with something called Egress. Did your, my data that I've spent all this time and money with my security team securing ever leave my hands, did it ever leave my secure VPC as they call it? >>And with these native integrations that we're building and about to unveil, here's kind of a sneak peek for, for next week at Data Citizens. We're now doing all compute and data operations in databases like Snowflake. And what that means is with no install and no configuration, you could log into the Collibra data quality app and have all of your data quality running inside the database that you've probably already picked as your your go forward team selection secured database of choice. So we're really excited about that. And I think if you look at the whole landscape of network cost, egress, cost, data storage and compute, what people are realizing is it's extremely efficient to do it in the way that we're about to release here next week. >>So this is interesting because what you just described, you know, you mentioned Snowflake, you mentioned Google, Oh actually you mentioned yeah, data bricks. You know, Snowflake has the data cloud. If you put everything in the data cloud, okay, you're cool, but then Google's got the open data cloud. If you heard, you know, Google next and now data bricks doesn't call it the data cloud, but they have like the open source data cloud. So you have all these different approaches and there's really no way up until now I'm, I'm hearing to, to really understand the relationships between all those and have confidence across, you know, it's like Jak Dani, you should just be a note on the mesh. And I don't care if it's a data warehouse or a data lake or where it comes from, but it's a point on that mesh and I need tooling to be able to have confidence that my data is governed and has the proper lineage, providence. And, and, and that's what you're bringing to the table, Is that right? Did I get that right? >>Yeah, that's right. And it's, for us, it's, it's not that we haven't been working with those great cloud databases, but it's the fact that we can send them the instructions now, we can send them the, the operating ability to crunch all of the calculations, the governance, the quality, and get the answers. And what that's doing, it's basically zero network costs, zero egress cost, zero latency of time. And so when you were to log into Big Query tomorrow using our tool or like, or say Snowflake for example, you have instant data quality metrics, instant profiling, instant lineage and access privacy controls, things of that nature that just become less onerous. What we're seeing is there's so much technology out there, just like all of the major brands that you mentioned, but how do we make it easier? The future is about less clicks, faster time to value, faster scale, and eventually lower cost. And, and we think that this positions us to be the leader there. >>I love this example because, you know, Barry talks about, wow, the cloud guys are gonna own the world and, and of course now we're seeing that the ecosystem is finding so much white space to add value, connect across cloud. Sometimes we call it super cloud and so, or inter clouding. All right, Kirk, give us your, your final thoughts and on on the trends that we've talked about and Data Citizens 22. >>Absolutely. Well, I think, you know, one big trend is discovery and classification. Seeing that across the board, people used to know it was a zip code and nowadays with the amount of data that's out there, they wanna know where everything is, where their sensitive data is. If it's redundant, tell me everything inside of three to five seconds. And with that comes, they want to know in all of these hyperscale databases how fast they can get controls and insights out of their tools. So I think we're gonna see more one click solutions, more SAS based solutions and solutions that hopefully prove faster time to value on, on all of these modern cloud platforms. >>Excellent. All right, Kurt Hasselbeck, thanks so much for coming on the Cube and previewing Data Citizens 22. Appreciate it. >>Thanks for having me, Dave. >>You're welcome. Right, and thank you for watching. Keep it right there for more coverage from the Cube. Welcome to the Cube's virtual Coverage of Data Citizens 2022. My name is Dave Valante and I'm here with Laura Sellers, who's the Chief Product Officer at Collibra, the host of Data Citizens. Laura, welcome. Good to see you. >>Thank you. Nice to be here. >>Yeah, your keynote at Data Citizens this year focused on, you know, your mission to drive ease of use and scale. Now when I think about historically fast access to the right data at the right time in a form that's really easily consumable, it's been kind of challenging, especially for business users. Can can you explain to our audience why this matters so much and what's actually different today in the data ecosystem to make this a reality? >>Yeah, definitely. So I think what we really need and what I hear from customers every single day is that we need a new approach to data management and our product teams. What inspired me to come to Calibra a little bit a over a year ago was really the fact that they're very focused on bringing trusted data to more users across more sources for more use cases. And so as we look at what we're announcing with these innovations of ease of use and scale, it's really about making teams more productive in getting started with and the ability to manage data across the entire organization. So we've been very focused on richer experiences, a broader ecosystem of partners, as well as a platform that delivers performance, scale and security that our users and teams need and demand. So as we look at, Oh, go ahead. >>I was gonna say, you know, when I look back at like the last 10 years, it was all about getting the technology to work and it was just so complicated. But, but please carry on. I'd love to hear more about this. >>Yeah, I, I really, you know, Collibra is a system of engagement for data and we really are working on bringing that entire system of engagement to life for everyone to leverage here and now. So what we're announcing from our ease of use side of the world is first our data marketplace. This is the ability for all users to discover and access data quickly and easily shop for it, if you will. The next thing that we're also introducing is the new homepage. It's really about the ability to drive adoption and have users find data more quickly. And then the two more areas of the ease of use side of the world is our world of usage analytics. And one of the big pushes and passions we have at Collibra is to help with this data driven culture that all companies are trying to create. And also helping with data literacy, with something like usage analytics, it's really about driving adoption of the CLE platform, understanding what's working, who's accessing it, what's not. And then finally we're also introducing what's called workflow designer. And we love our workflows at Libra, it's a big differentiator to be able to automate business processes. The designer is really about a way for more people to be able to create those workflows, collaborate on those workflow flows, as well as people to be able to easily interact with them. So a lot of exciting things when it comes to ease of use to make it easier for all users to find data. >>Y yes, there's definitely a lot to unpack there. I I, you know, you mentioned this idea of, of of, of shopping for the data. That's interesting to me. Why this analogy, metaphor or analogy, I always get those confused. I let's go with analogy. Why is it so important to data consumers? >>I think when you look at the world of data, and I talked about this system of engagement, it's really about making it more accessible to the masses. And what users are used to is a shopping experience like your Amazon, if you will. And so having a consumer grade experience where users can quickly go in and find the data, trust that data, understand where the data's coming from, and then be able to quickly access it, is the idea of being able to shop for it, just making it as simple as possible and really speeding the time to value for any of the business analysts, data analysts out there. >>Yeah, I think when you, you, you see a lot of discussion about rethinking data architectures, putting data in the hands of the users and business people, decentralized data and of course that's awesome. I love that. But of course then you have to have self-service infrastructure and you have to have governance. And those are really challenging. And I think so many organizations, they're facing adoption challenges, you know, when it comes to enabling teams generally, especially domain experts to adopt new data technologies, you know, like the, the tech comes fast and furious. You got all these open source projects and get really confusing. Of course it risks security, governance and all that good stuff. You got all this jargon. So where do you see, you know, the friction in adopting new data technologies? What's your point of view and how can organizations overcome these challenges? >>You're, you're dead on. There's so much technology and there's so much to stay on top of, which is part of the friction, right? It's just being able to stay ahead of, of and understand all the technologies that are coming. You also look at as there's so many more sources of data and people are migrating data to the cloud and they're migrating to new sources. Where the friction comes is really that ability to understand where the data came from, where it's moving to, and then also to be able to put the access controls on top of it. So people are only getting access to the data that they should be getting access to. So one of the other things we're announcing with, with all of the innovations that are coming is what we're doing around performance and scale. So with all of the data movement, with all of the data that's out there, the first thing we're launching in the world of performance and scale is our world of data quality. >>It's something that Collibra has been working on for the past year and a half, but we're launching the ability to have data quality in the cloud. So it's currently an on-premise offering, but we'll now be able to carry that over into the cloud for us to manage that way. We're also introducing the ability to push down data quality into Snowflake. So this is, again, one of those challenges is making sure that that data that you have is d is is high quality as you move forward. And so really another, we're just reducing friction. You already have Snowflake stood up. It's not another machine for you to manage, it's just push down capabilities into Snowflake to be able to track that quality. Another thing that we're launching with that is what we call Collibra Protect. And this is that ability for users to be able to ingest metadata, understand where the PII data is, and then set policies up on top of it. So very quickly be able to set policies and have them enforced at the data level. So anybody in the organization is only getting access to the data they should have access to. >>Here's Topica data quality is interesting. It's something that I've followed for a number of years. It used to be a back office function, you know, and really confined only to highly regulated industries like financial services and healthcare and government. You know, you look back over a decade ago, you didn't have this worry about personal information, g gdpr, and, you know, California Consumer Privacy Act all becomes, becomes so much important. The cloud is really changed things in terms of performance and scale and of course partnering for, for, with Snowflake it's all about sharing data and monetization, anything but a back office function. So it was kind of smart that you guys were early on and of course attracting them and as a, as an investor as well was very strong validation. What can you tell us about the nature of the relationship with Snowflake and specifically inter interested in sort of joint engineering or, and product innovation efforts, you know, beyond the standard go to market stuff? >>Definitely. So you mentioned there were a strategic investor in Calibra about a year ago. A little less than that I guess. We've been working with them though for over a year really tightly with their product and engineering teams to make sure that Collibra is adding real value. Our unified platform is touching pieces of our unified platform or touching all pieces of Snowflake. And when I say that, what I mean is we're first, you know, able to ingest data with Snowflake, which, which has always existed. We're able to profile and classify that data we're announcing with Calibra Protect this week that you're now able to create those policies on top of Snowflake and have them enforce. So again, people can get more value out of their snowflake more quickly as far as time to value with, with our policies for all business users to be able to create. >>We're also announcing Snowflake Lineage 2.0. So this is the ability to take stored procedures in Snowflake and understand the lineage of where did the data come from, how was it transformed with within Snowflake as well as the data quality. Pushdown, as I mentioned, data quality, you brought it up. It is a new, it is a, a big industry push and you know, one of the things I think Gartner mentioned is people are losing up to $15 million without having great data quality. So this push down capability for Snowflake really is again, a big ease of use push for us at Collibra of that ability to, to push it into snowflake, take advantage of the data, the data source, and the engine that already lives there and get the right and make sure you have the right quality. >>I mean, the nice thing about Snowflake, if you play in the Snowflake sandbox, you, you, you, you can get sort of a, you know, high degree of confidence that the data sharing can be done in a safe way. Bringing, you know, Collibra into the, into the story allows me to have that data quality and, and that governance that I, that I need. You know, we've said many times on the cube that one of the notable differences in cloud this decade versus last decade, I mean ob there are obvious differences just in terms of scale and scope, but it's shaping up to be about the strength of the ecosystems. That's really a hallmark of these big cloud players. I mean they're, it's a key factor for innovating, accelerating product delivery, filling gaps in, in the hyperscale offerings cuz you got more stack, you know, mature stack capabilities and you know, it creates this flywheel momentum as we often say. But, so my question is, how do you work with the hyperscalers? Like whether it's AWS or Google, whomever, and what do you see as your role and what's the Collibra sweet spot? >>Yeah, definitely. So, you know, one of the things I mentioned early on is the broader ecosystem of partners is what it's all about. And so we have that strong partnership with Snowflake. We also are doing more with Google around, you know, GCP and kbra protect there, but also tighter data plex integration. So similar to what you've seen with our strategic moves around Snowflake and, and really covering the broad ecosystem of what Collibra can do on top of that data source. We're extending that to the world of Google as well and the world of data plex. We also have great partners in SI's Infosys is somebody we spoke with at the conference who's done a lot of great work with Levi's as they're really important to help people with their whole data strategy and driving that data driven culture and, and Collibra being the core of it. >>Hi Laura, we're gonna, we're gonna end it there, but I wonder if you could kind of put a bow on, you know, this year, the event your, your perspectives. So just give us your closing thoughts. >>Yeah, definitely. So I, I wanna say this is one of the biggest releases Collibra's ever had. Definitely the biggest one since I've been with the company a little over a year. We have all these great new product innovations coming to really drive the ease of use to make data more valuable for users everywhere and, and companies everywhere. And so it's all about everybody being able to easily find, understand, and trust and get access to that data going forward. >>Well congratulations on all the pro progress. It was great to have you on the cube first time I believe, and really appreciate you, you taking the time with us. >>Yes, thank you for your time. >>You're very welcome. Okay, you're watching the coverage of Data Citizens 2022 on the cube, your leader in enterprise and emerging tech coverage. >>So data modernization oftentimes means moving some of your storage and computer to the cloud where you get the benefit of scale and security and so on. But ultimately it doesn't take away the silos that you have. We have more locations, more tools and more processes with which we try to get value from this data. To do that at scale in an organization, people involved in this process, they have to understand each other. So you need to unite those people across those tools, processes, and systems with a shared language. When I say customer, do you understand the same thing as you hearing customer? Are we counting them in the same way so that shared language unites us and that gives the opportunity for the organization as a whole to get the maximum value out of their data assets and then they can democratize data so everyone can properly use that shared language to find, understand, and trust the data asset that's available. >>And that's where Collibra comes in. We provide a centralized system of engagement that works across all of those locations and combines all of those different user types across the whole business. At Collibra, we say United by data and that also means that we're united by data with our customers. So here is some data about some of our customers. There was the case of an online do it yourself platform who grew their revenue almost three times from a marketing campaign that provided the right product in the right hands of the right people. In other case that comes to mind is from a financial services organization who saved over 800 K every year because they were able to reuse the same data in different kinds of reports and before there was spread out over different tools and processes and silos, and now the platform brought them together so they realized, oh, we're actually using the same data, let's find a way to make this more efficient. And the last example that comes to mind is that of a large home loan, home mortgage, mortgage loan provider where they have a very complex landscape, a very complex architecture legacy in the cloud, et cetera. And they're using our software, they're using our platform to unite all the people and those processes and tools to get a common view of data to manage their compliance at scale. >>Hey everyone, I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizens. Stan, it's great to have you back on the cube. >>Hey Lisa, nice to be. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, it's so much more than technology innovation. It also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow gonna to be a data citizen, right? So you need to make sure that these people are aware of it. You need that. People have skills and competencies to do with data what necessary and that's on, all right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in dashboard to actually make that decision and take that action. Right? >>And once you have that why to the organization, that's when you have a good data culture. Now that's continuous effort for most organizations because they're always moving, somehow they're hiring new people and it has to be continuous effort because we've seen that on the hand. Organizations continue challenged their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefit. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example, and we did an IDC study earlier this year, quite interesting. I can recommend anyone to it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, ok, I'm doing this, you know, data culture for everyone, awakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this re reasons you're trying to bring both of those together and the ones that get data intelligence right, are successful and competitive. That's, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, the organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, laptops, what have you, you're not using those, right? Or you know, you're delivering them throughout organization, but not enabling your colleagues to actually do something with that asset. Same thing as through with data today, right? If you're not properly using the data asset and competitors are, they're gonna to get more advantage. So as to how you get this done, establish this. There's angles to look at, Lisa. So one angle is obviously the leadership whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? So I'm just gonna summarize it as a data leader for a second. >>So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can leadership in the organization and also the business value. And that's important. Cause those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You, I really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities such as a data intelligence platform like s then the in place to really start upgrading that culture inch by inch if you'll, >>Yes, I like that. The recipe for success. So you are the co-founder of Collibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Calibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speaks here, are very excited. You know, we have Barb from m MIT speaking about data monetization. We have Dilla at the last minute. So really exciting agen agenda. Can't wait to get back out there essentially. So over the years at, we've doing this since two and eight, so a good years and I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, if you, so everybody's wearing all sorts of hat at time. But over the years I've run, you know, presales that sales partnerships, product cetera. And as our company got a little bit biggish, we're now thousand two. Something like people in the company. >>I believe systems and processes become a lot important. So we said you CBRA isn't the size our customers we're getting there in of organization structure, process systems, et cetera. So we said it's really time for us to put our money where is and to our own data office, which is what we were seeing customers', organizations worldwide. And they organizations have HR units, they have a finance unit and over time they'll all have a department if you'll, that is responsible somehow for the data. So we said, ok, let's try to set an examples that other people can take away with it, right? Can take away from it. So we set up a data strategy, we started building data products, took care of the data infrastructure. That's sort of good stuff. And in doing all of that, ISA exactly as you said, we said, okay, we need to also use our product and our own practices and from that use, learn how we can make the product better, learn how we make, can make the practice better and share that learning with all the, and on, on the Monday mornings, we sometimes refer to eating our dog foods on Friday evenings. >>We referred to that drinking our own champagne. I like it. So we, we had a, we had the driver to do this. You know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should, this is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders, if you'll or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure that the products, the data products can run, the data can flow and you know, the quality can be checked. >>And then we have a data intelligence or data governance builders where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the CBRA approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? And how can data help overcome those challenges? And from those use cases, we then just started to build a map and started execution use of the use case. And a important ones are very simple. We them with our, our customers as well, people talking about the cata, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and privacy. So they have their process registry and they can see how the data flows. >>So that's a starting place and that turns into a marketplace so that if new analysts and data citizens join kbra, they immediately have a place to go to, to look at, see, ok, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? So they can immediately get access data. And another one that we is around trusted business. We're seeing that since, you know, self-service BI allowed everyone to make beautiful dashboards, you know, pie, pie charts. I always, my pet pee is the pie chart because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted this reporting. So we know if a, the dashboard, a data product essentially is built, we not that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either, Right. And that silver browser, right? Absolutely >>Decay. >>Exactly. Yes, >>Absolutely. Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with to your organization, but there's a few that we use that might be of interest. Use those pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Are the, is the data platform up and running? Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption's a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data sciences and products. Are people using them? Are they getting value from it? >>Can we calculate that value in ay perspective, right? Yeah. So that we can to the rest of the business continue to say we're tracking all those numbers and those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or, or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so and so forth. So these are an set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in thousand 10 there may have been like 10 achieve data officers or something. Gartner has exact numbers on them, but then they grew, you know, industries and the number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data. So you'll see over the years that's gonna evolve more digital and more data products. So for next years, my, my prediction is it's all products because it's an immediate link between data and, and the essentially, right? Right. So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. I think there's gonna be a continued challenge for the chief officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not, right? >>So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful and the ones who get that will the ones that do it on the basis of data monetization, right? Connecting value to the data and making that value clear to all the data citizens in the organization, right? And in that sense, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an asset. >>Absolutely. Because there's so much value that can be extracted. Organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful and being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the cube at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage. >>Okay, this concludes our coverage of Data Citizens 2022, brought to you by Collibra. Remember, all these videos are available on demand@thecube.net. And don't forget to check out silicon angle.com for all the news and wiki bod.com for our weekly breaking analysis series where we cover many data topics and share survey research from our partner ETR Enterprise Technology Research. If you want more information on the products announced at Data Citizens, go to collibra.com. There are tons of resources there. You'll find analyst reports, product demos. It's really worthwhile to check those out. Thanks for watching our program and digging into Data Citizens 2022 on the Cube, your leader in enterprise and emerging tech coverage. We'll see you soon.

>>Hey everyone. I'm Lisa Martin covering Data Citizens 22, brought to you by Collibra. This next conversation is gonna focus on the importance of data culture. One of our Cube alumni is back, Stan Christians is Collibra's co-founder and it's Chief Data citizen. Stan, it's great to have you back on the cube. >>Hey, Lisa, nice to be here. >>So we're gonna be talking about the importance of data culture, data intelligence, maturity, all those great things. When we think about the data revolution that every business is going through, you know, so much more than technology innovation, it also really re requires cultural transformation, community transformation. Those are challenging for customers to undertake. Talk to us about what you mean by data citizenship and the role that creating a data culture plays in that journey. >>Right. So as you know, our event is called Data Citizens because we believe that in the end, a data citizen is anyone who uses data to do their job. And we believe that today's organizations, you have a lot of people, most of the employees in an organization are somehow going to be a data citizen, right? So you need to make sure that these people are aware of it. You need to make sure that these people have the skills and competencies to do with data what is necessary. And that's on all levels, right? So what does it mean to have a good data culture? It means that if you're building a beautiful dashboard to try and convince your boss, we need to make this decision that your boss is also open to and able to interpret, you know, the data presented in that dashboard to actually make that decision and take that action, right? >>And once you have that why through the organization, that's when you have a good data culture. Now, that's a continuous effort for most organizations because they, they're always moving, somehow there, hiring new people. And it has to be a continuous effort because we've seen that on the one hand, organizations continue to be challenged with controlling their data sources and where all the data is flowing, right? Which in itself creates a lot of risk. But also on the other set hand of the equation, you have the benefits. You know, you might look at regulatory drivers like, we have to do this, right? But it's, it's much better right now to consider the competitive drivers, for example. And we did an IDC study earlier this year, quite interesting. I can recommend anyone to read it. And one of the conclusions they found as they surveyed over a thousand people across organizations worldwide is that the ones who are higher in maturity. >>So the, the organizations that really look at data as an asset, look at data as a product and actively try to be better at it, don't have three times as good a business outcome as the ones who are lower on the maturity scale, right? So you can say, Okay, I'm doing this, you know, data culture for everyone, wakening them up as data citizens. I'm doing this for competitive reasons, I'm doing this for regulatory reasons. You're trying to bring both of those together and the ones that get data intelligence right, are just going to be more successful and more competitive. That's our view, and that's what we're seeing out there in the market. >>Absolutely. We know that just generally stand right, The organizations that are, are really creating a, a data culture and enabling everybody within the organization to become data citizens are, We know that in theory they're more competitive, they're more successful. But the IDC study that you just mentioned demonstrates they're three times more successful and competitive than their peers. Talk about how Collibra advises customers to create that community, that culture of data when it might be challenging for an organization to adapt culturally. >>Of course, of course it's difficult for an organization to adapt, but it's also necessary, as you just said, imagine that, you know, you're a modern day organization, phones, laptops, what have you, you're not using those IT assets, right? Or you know, you're delivering them through your, throughout the organization, but not enabling your colleagues to actually do something with that asset. Same thing is true with data today, right? If you are not properly using the data assets and your competitors are, they're going to get more advantage. So as to how you get this zone or how you establish this culture, there's a few angles to look at. I would say, Lisa, so one angle is obviously the leadership angle whereby whoever is the boss of data in the organization, you typically have multiple bosses there, like achieve data officers. Sometimes there's, there's multiple, but they may have a different title, right? >>So I'm just gonna summarize it as a data leader for a second. So whoever that is, they need to make sure that there's a clear vision, a clear strategy for data. And that strategy needs to include the monetization aspect. How are you going to get value from data? Yes. Now that's one part because then you can clearly see the example of your leadership in the organization and also the business value. And that's important because those people, their job in essence really is to make everyone in the organization think about data as an asset. And I think that's the second part of the equation of getting that culture right, is it's not enough to just have that leadership out there, but you also have to get the hearts and minds of the data champions across the organization. You really have to win them over. And if you have those two combined and obviously a good technology to, you know, connect those people and have them execute on their responsibilities, such as as a data intelligence platform like Colibra, then you have the pieces in place to really start upgrading that culture inch by inch if youll, >>Yes, I like that. The recipe for success. So you are the co-founder of colibra. You've worn many different hats along this journey. Now you're building Collibra's own data office. I like how before we went live, we were talking about Collibra is drinking its own champagne. I always loved to hear stories about that. You're speaking at Data Citizens 2022. Talk to us about how you are building a data culture within Collibra and what maybe some of the specific projects are that Collibra's data office is working on. >>Yes, and it is indeed data citizens. There are a ton of speakers here, very excited. You know, we have Barb from MIT speaking about data monetization. We have dig pat at the last minute on the agenda. So really exciting agenda. Can't wait to get back out there. But essentially you're right. So over the years at cbra, we've been doing this now since 2008, so a good 15 years. And I think we have another decade of work ahead in the market, just to be very clear. Data is here to stick around as are we. And myself, you know, when you start a company, we were for people in a, in a garage if you will. So everybody's wearing all sorts of hat at that time. But over the years I've run, you know, pre-sales at colibra, I've run post-sales partnerships, product, et cetera. And as our company got a little bit biggish for now, 1,200, something like that, people in the company, I believe systems and processes become a lot more important, right? >>So we said, you know, Colibra isn't the size of our customers yet, but we're getting there in terms of organizations, structure, process systems, et cetera. So we said, it's really time for us to put our money where our mouth is and to set up our own data office, which is what we were seeing at all of our customers are doing, and which is what we're seeing that organizations worldwide are doing. And Gartner was predicting us as well. They said, Okay, organizations have an HR unit, they have a finance unit, and over time they'll all have a department, if you will, that is responsible somehow for the data. So we said, Okay, let's try to set a an example at cbra. Let's try to set up our own data office and such way that other people can take away with it, right? Can take away from it. >>So we set up a data strategy, we started building data products, took care of the data infrastructure, that sort of good stuff. And in doing all of that, Lisa, exactly as you said, we said, okay, we need to also use our own product and our own practices, right? And from that use, learn how we can make the product better, learn how we can make the practice better, and share that learning with all of the markets of course. And on, on the Monday mornings, we sometimes refer to that as eating our own dog foods or Friday evenings we refer to that as drinking our own champagne. I like it. So we, we had a, we had the driver to do this, you know, there's a clear business reason. So we involved, we included that in the data strategy and that's a little bit of our origin. >>Now how, how do we organize this? We have three pillars, and by no means is this a template that everyone should follow? This is just the organization that works at our company, but it can serve as an inspiration. So we have a pillar, which is data science. The data product builders if you will, or the people who help the business build data products. We have the data engineers who help keep the lights on for that data platform to make sure the products, the data products can run, the data can flow and you know, the quality can be checked. And then we have a data intelligence or data governance builder where we have those data governance, data intelligence stakeholders who help the business as a sort of data partner to the business stakeholders. So that's how we've organized it. And then we started following the calibra approach, which is, well, what are the challenges that our business stakeholders have in hr, finance, sales, marketing all over? >>And how can data help overcome those challenges? And from those use cases, we then just started to build a roadmap and started execution on use case after use case. And a few important ones there are very simple, we see them with our, all our customers as well. People love talking about the catalog, right? The catalog for the data scientists to know what's in their data lake, for example, and for the people in and legal and privacy. So they have their process registry and they can see how the data flows. So that's a popular starting place. And that turns into a marketplace so that if new analysts and data citizens join cbra, they immediately have a place to go to, to look and see, okay, what data is out there for me as an analyst or a data scientist or whatever to do my job, right? >>So they can immediately get access to the data. And another one that we did is around trusted business reporting. We're seeing that since 2008. You know, self-service BI allowed everyone to make beautiful dashboards, you know, by pie charts. I always, my pet peeve is the pie charts because I love buy and you shouldn't always be using pie charts. But essentially there's become proliferation of those reports. And now executives don't really know, okay, should I trust this report or that report the reporting on the same thing. But the numbers seem different, right? So that's why we have trusted business reporting. So we know if a report, a dashboard, a data product essentially is built, we know that all the right steps are being followed and that whoever is consuming that can be quite confident in the result either right, in that silver or browser Absolutely key. Exactly. Yes. A absolutely. >>Talk a little bit about some of the, the key performance indicators that you're using to measure the success of the data office. What are some of those KPIs? >>KPIs and measuring is a big topic in the, in the data chief data officer profession, I would say, and again, it always varies with respect to your organization, but there's a few that we use that might be of interest to you. So remember we have those three pillars, right? And we have metrics across those pillars. So for example, a pillar on the data engineering side is gonna be more related to that uptime, right? Audit is a data platform up and running. Are the data products up and running? Is the quality in them good enough? Is it going up? Is it going down? What's the usage? But also, and especially if you're in the cloud and if consumption is a big thing, you have metrics around cost, for example, right? So that's one set of examples. Another one is around the data science and the products. >>Are people using them? Are they getting value from it? Can we calculate that value in a monetary perspective, right? So that we can to the rest of the business continue to say we're tracking on those numbers. And those numbers indicate that value is generated and how much value estimated in that region. And then you have some data intelligence, data governance metrics, which is, for example, you have a number of domains in a data mesh. People talk about being the owner of a data domain, for example, like product or customer. So how many of those domains do you have covered? How many of them are already part of the program? How many of them have owners assigned? How well are these owners organized, executing on their responsibilities? How many tickets are open closed? How many data products are built according to process? And so on and so forth. So these are an a set of examples of, of KPIs. There's a, there's a lot more, but hopefully those can already inspire the audience. >>Absolutely. So we've, we've talked about the rise of cheap data offices, it's only accelerating. You mentioned this is like a 10 year journey. So if you were to look into a crystal ball, what do you see in terms of the maturation of data offices over the next decade? >>So we, we've seen indeed the, the role sort of grow up, I think in, in 2010 there may have been like 10 chief data officers or something. Gartner has exact numbers on them, but then they grew, you know, 400, they were like mostly in financial services, but they expanded then to all of industries and then to all of the season. The number is estimated to be about 20,000 right now. Wow. And they evolved in a sort of stack of competencies, defensive data strategy, because the first chief data officers were more regulatory driven, offensive data strategy support for the digital program. And now all about data products, right? So as a data leader, you'd now need all of those competences and need to include them in, in your strategy. >>How is that going to evolve for the next couple of years? I wish I had one of those crystal balls, right? But essentially I think for the next couple of years there's gonna be a lot of people, you know, still moving along with those four levels of the stack. A lot of people I see are still in version one and version two of the chief data officer. So you'll see over the years that's going to evolve more digital and more data products. So for next three, five years, my, my prediction is it's all going to be about data products because it's an immediate link between the data and, and the dollar essentially, right? So that's gonna be important and quite likely a new, some new things will be added on, which nobody can predict yet. But we'll see those pop up in a few years. >>I think there's gonna be a continued challenge for the chief data officer role to become a real executive role as opposed to, you know, somebody who claims that they're executive, but then they're not. Right? So the real reporting level into the board, into the CEO for example, will continue to be a challenging point. But the ones who do get that done will be the ones that are successful. Yeah. And the ones who get that done will be the ones that do it on the basis of data monetization, right? Connecting value to the data and making that very clear to all the data citizens in the organization, right? Really and in that sense, value chain, they'll need to have both, you know, technical audiences and non-technical audiences aligned of course. And they'll need to focus on adoption. Again, it's not enough to just have your data office be involved in this. It's really important that you're waking up data citizens across the organization and you make everyone in the organization think about data as an essence. >>Absolutely. Because there's so much value that can be extracted if organizations really strategically build that data office and democratize access across all those data citizens. Stan, this is an exciting arena. We're definitely gonna keep our eyes on this. Sounds like a lot of evolution and maturation coming from the data office perspective. From the data citizen perspective. And as the data show that you mentioned in that IDC study, you mentioned Gartner as well, organizations have so much more likelihood of being successful in being competitive. So we're gonna watch this space. Stan, thank you so much for joining me on the queue at Data Citizens 22. We appreciate it. >>Thanks for having me over >>From Data Citizens 22, I'm Lisa Martin, you're watching The Cube, the leader in live tech coverage.

>>Hey everyone. Welcome back to the cubes day two coverage of VMware Explorer, 22 from San Francisco. Lisa Martin, back here with you with Dave Nicholson, we have a couple of guests from VMware. Joining us, please. Welcome Jay Workman, senior director, cloud partner, and alliances marketing, and Jeff Thompson, VP cloud provider sales at VMware guys. It's great to have you on the program. >>Ah, good to be here. Thanks for having us on. >>We're gonna be talking about a really interesting topic. Sovereign cloud. What is sovereign cloud? Jeff? Why is it important, but fundamentally, what is >>It? Yeah, well, we were just talking a second ago. Aren't we? And it's not about royalty. So yeah, data sovereignty is really becoming super important. It's about the regulation and control of data. So lots of countries now are being very careful and advising companies around where to place data and the jurisdictional controls mandate that personal data or otherwise has to be secured. We ask, we have to have access controls around it and privacy controls around it. So data sovereign clouds are clouds that have been built by our cloud providers in, in, in VMware that specifically satisfy the requirements of those jurisdictions and regulated industries. So we've built a, a little program around that. We launched it about a year ago and continuing to add cloud providers to that. >>Yeah, and I, I think it's also important just to build on what Jeff said is, is who can access that data is becoming increasingly important data is, is almost in it's. It is becoming a bit of a currency. There's a lot of value in data and securing that data is, is becoming over the years increasingly important. So it's, it's not like we built a problem or we created a solution for problem that didn't exist. It's gotten it's, it's been a problem for a while. It's getting exponentially bigger data is expanding and growing exponentially, and it's becoming increasingly important for organizations and companies to realize where my data sits, who can access it, what types of data needs to go and what type of clouds. And it's very, very aligned with multi-cloud because some data can sit in a, in a public cloud, which is fine, but some data needs to be secure. It needs to be resident within country. And so this is, this is what we're addressing through our partners. >>Yeah, I, yeah, I was just gonna add to that. I think there's a classification there there's data residency, and then there's data sovereignty. So residency is just about where is the data, which country is it in sovereignty is around who can access that data. And that's the critical aspect of, of data sovereignty who's got control and access to that data. And how do we make sure that all the controls are in place to make sure that only the right people can get access to that data? Yeah. >>So let's, let's sort of build from the ground up an example, and let's use Western Europe as an example, just because state to state in the United States, although California is about to adopt European standards for privacy in a, in a unique, in a unique, unique way, pick a country in, in Europe, I'm a service provider. I have an offering and that offering includes a stack of hardware and I'm running what we frequently refer to as the STDC or software defined data center stack. So I've got NEX and I've got vs N and I've got vSphere and I'm running and I have a cloud and you have all of the operational tools around that, and you can spin up VMs and render under applications there. And here we are within the borders of this country, what makes it a sovereign cloud at that? So at that point, is that a sovereign cloud or? >>No, not yet. Not it's close. I mean, you nailed, >>What's >>A secret sauce. You nailed the technology underpinning. So we've got 4,500 plus cloud provider partners around the world. Less than 10% of those partners are running the full STDC stack, which we've branded as VMware cloud verified. So the technology underpinning from our perspective is the starting point. Okay. For sovereignty. So they, they, they need that right. Technology. Okay. >>Verified is required for sovereign. Yes. >>Okay. Cloud verified is the required technology stack for sovereign. So they've got vSphere vs. A NSX in there. Okay. A lot of these partners are also offering a multitenant cloud with VMware cloud director on top of that, which is great. That's the starting point. But then we've, we've set a list of standards above and beyond that, in addition to the technology, they've gotta meet certain jurisdiction requirements, certain local compliance requirements and certifications. They've gotta be able to address the data re data residency requirements of their particular jurisdiction. So it's going above and beyond. But to your point, it does vary by country. >>Okay. So, so in this hypothetical example, this is this country. You a stand, I love it. When people talk about Stan, people talk about EMIA and you know, I, I love AMEA food. Isn't AIAN food. One. There's no such thing as a European until you have an Italian, a Britain, a German yep. In Florida arguing about how our beer and our coffee is terrible. Right. Right. Then they're all European. They go home and they don't like each other. Yeah. So, but let's just pretend that there's a thing called Europe. So this, so there's this, so we've got a border, we know residency, right. Because it physically is here. Yep. But what are the things in terms of sovereignty? So you're talking about a lot of kind of certification and validation, making sure that, that everything maps to those existing rules. So is, this is, this is a lot of this administrative and I mean, administrative in the, in the sort of state administrative terminology, >>I I'm let's build on your example. Yeah. So we were talking about food and obviously we know the best food in the world comes from England. >>Of course it does. Yeah. I, no doubt. I agree. I Don not get that. I do. I do do agree. Yeah. >>So UK cloud, fantastic partner for us. Okay. Whether they're one of our first sovereign cloud providers in the program. So UK cloud, they satisfied the requirements with the local UK government. They built out their cloud verified. They built out a stack specifically that enables them to satisfy the requirements of being a sovereign cloud provider. They have local data centers inside the UK. The data from the local government is placed into those data centers. And it's managed by UK people on UK soil so that they know the privacy, they know the security aspects, the compliance, all of that wrapped up on top of a secure SDDC platform. Okay. Satisfies the requirements of the UK government, that they are managing that data in a sovereign way that, that, that aligns to the jurisdictional control that they expect from a company like UK cloud. Well, >>I think to build on that, a UK cloud is an example of certain employees at UK, UK cloud will have certain levels of clearance from the UK government who can access and work on certain databases that are stored within UK cloud. So they're, they're addressing it from multiple fronts, not just with their hardware, software data center framework, but actually at the individual compliance level and individual security clearance level as to who can go in and work on that data. And it's not just a governmental, it's not a public sector thing. I mean, any highly regulated industry, healthcare, financial services, they're all gonna need this type of data protection and data sovereignty. >>Can this work in a hyperscaler? So you've got you, have, you have VMC AVS, right? GC V C >>O >>CVAs O CVS. Thank you. Can it be, can, can a sovereign cloud be created on top of physical infrastructure that is in one of those hyperscalers, >>From our perspective, it's not truly sovereign. If, if it's a United States based company operating in Germany, operating in the UK and a local customer or organization in Germany, or the UK wants to deploy workloads in that cloud, we wouldn't classify that as totally sovereign. Okay. Because by virtue of the cloud act in the United States, that gives the us government rights to request or potentially view some of that data. Yeah. Because it's, it's coming out of a us based operator data center sitting on foreign soil so that the us government has some overreach into that. And some of that data may actually be stored. Some of the metadata may reside back in the us and the customer may not know. So certain workloads would be ideally suited for that. But for something that needs to be truly sovereign and local data residency, that it wouldn't be a good fit. I think that >>Perspectives key thing, going back to residency versus sovereignty. Yeah. It can be, let's go to our UK example. It can be on a hyperscaler in the UK now it's resident in the UK, but some of the metadata, the profiling information could be accessible by the entity in the United States. For example, there now it's not sovereign anymore. So that's the key difference between a, what we view as a pro you know, a pure sovereign cloud play and then maybe a hyperscaler that's got more residency than sovereignty. >>Yeah. We talk a lot about partnerships. This seems to be a unique opportunity for a certain segment of partners yeah. To give that really is an opportunity for them to have a line of business established. That's unique from some of the hyperscale cloud providers. Yeah. Where, where sort of the, the modesty of your size might be an advantage if you're in a local. Yes. You're in Italy and you are a service provider. There sounds like a great fit, >>That's it? Yeah. You've always had the, the beauty of our program. We have 4,500 cloud providers and obviously not, all of them are able to provide a data, a sovereign cloud. We have 20 in the program today in, in the country. You you'd expect them to be in, you know, the UK, Italy, Italy, France, Germany, over in Asia Pacific. We have in Australia and New Zealand, Japan, and, and we have Canada and Latin America to, to dovetail, you know, the United States. But those are the people that have had these long term relationships with the local governments, with these regulated industries and providing those services for many, many years. It's just that now data sovereignty has become more important. And they're able to go that extra mile and say, Hey, we've been doing this pretty much, you know, for decades, but now we're gonna put a wrap and some branding around it and do these extra checks because we absolutely know that we can provide the sovereignty that's required. >>And that's been one of the beautiful things about the entire initiative is we're actually, we're learning a lot from our partners in these countries to Jeff's point have been doing this. They've been long time, VMware partners they've been doing sovereignty. And so collectively together, we're able to really establish a pretty robust framework from, from our perspective, what does data sovereignty mean? Why does it matter? And then that's gonna help us work with the customers, help them decide which workloads need to go and which type of cloud. And it dovetails very, very nicely into a multi-cloud that's a reality. So some of those workloads can sit in the public sector and the hyperscalers and some of 'em need to be sovereign. Yeah. So it's, it's a great solution for our customers >>When you're in customer conversations, especially as, you know, data sovereign to be is becomes a global problem. Where, who are you talking to? Are you talking to CIOs? Are you talking to chief data officers? I imagine this is a pretty senior level conversation. >>Yeah. I it's, I think it's all of the above. Really. It depends. Who's managing the data. What type of customer is it? What vertical market are they in? What compliance regulations are they are they beholden to as a, as an enterprise, depending on which country they're in and do they have a need for a public cloud, they may already be all localized, you know? So it really depends, but it, it could be any of those. It's generally I think a fair, fairly senior level conversation. And it's, it's, it's, it's consultancy, it's us understanding what their needs are working with our partners and figuring out what's the best solution for them. >>And I think going back to, they've probably having those conversations for a long time already. Yeah. Because they probably have had workloads in there for years, maybe even decades. It's just that now sovereignty has become, you know, a more popular, you know, requirements to satisfy. And so they've gone going back to, they've gone the extra mile with those as the trusted advisor with those people. They've all been working with for many, many years to do that work. >>And what sort of any examples you mentioned some of the highly regulated industries, healthcare, financial services, any customer come to mind that you think really articulates the value of what VMware's delivering through its service through its cloud provider program. That makes the obvious why VMware an obvious answer? >>Wow. I, I, I get there's, there's so many it's, it's actually, it's each of our different cloud providers. They bring their win wise to us. And we just have, we have a great library now of assets that are on our sovereign cloud website of those win wires. So it's many industries, many, many countries. So you can really pick, pick your, your choice. There. That's >>A good problem >>To have, >>To the example of UK cloud they're, they're really focused on the UK government. So some of them aren't gonna be referenced. Well, we may have indication of a major financial services company in Australia has deployed with AU cloud, one of our partners. So we we've also got some semi blind references like that. And, and to some degree, a lot of these are maintained as fairly private wins and whatnot for obvious security reasons, but, and we're building it and building that library up, >>You mentioned the number 4,500, a couple of times, you, you referencing VMware cloud provider partners or correct program partners. So VCP P yes. So 45, 4500 is the, kind of, is the, is the number, you know, >>That's the number >>Globally of our okay. >>Partners that are offering a commercial cloud service based at a minimum with vSphere and they're. And many of 'em have many more of our technologies. And we've got little under 10% of those that have the cloud verified designation that are running that full STDC, stack >>Somebody, somebody Talli up, all of that. And the argument has been made that, that rep that, that would mean that VMware cloud. And although some of it's on IAS from hyperscale cloud providers. Sure. But that, that rep, that means that VMware has the third or fourth largest cloud on the planet already right now. >>Right. Yep. >>Which is kind of interesting because yeah. If you go back to when, what 2016 or so when VMC was at least baned about yeah. Is that right? A lot of people were skeptical. I was skeptical very long history with VMware at the time. And I was skeptical. I I'm thinking, nah, it's not gonna work. Yeah. This is desperation. Sorry, pat. I love you. But it's desperation. Right. AWS, their attitude is in this transaction. Sure. Send us some customers we'll them. Yeah. Right. I very, very cynical about it. Completely proved me wrong. Obviously. Where did it go? Went from AWS to Azure to right. Yeah. To GCP, to Oracle, >>Oracle, Alibaba, >>Alibaba. Yep. Globally. >>We've got IBM. Yep. Right. >>Yeah. So along the way, it would be easy to look at that trajectory and say, okay, wow, hyperscale cloud. Yeah. Everything's consolidating great. There's gonna be five or six or 10 of these players. And that's it. And everybody else is out in the cold. Yeah. But it turns out that long tail, if you look at the chart of who the largest VCP P partners are, that long tail of the smaller ones seem to be carving out specialized yes. Niches where you can imagine now, at some point in the future, you sum up this long tail and it becomes larger than maybe one of the hyperscale cloud providers. Right. I don't think a lot of people predicted that. I think, I think people predicted the demise of VMware and frankly, a lot of people in the VMware ecosystem, just like they predicted the demise of the mainframe. Sure. The storage area network fill in the blank. I >>Mean, Jeff and I we've oh yeah. We've been on the, Jeff's been a little longer than I have, but we've been working together for 10 plus years on this. And we've, we've heard that many times. Yeah. Yeah. Our, our ecosystem has grown over the years. We've seen some consolidation, some M and a activity, but we're, we're not even actively recruiting partners and it's growing, we're focused on helping our partners gain more, share internally, gain, more share at wallet, but we're still getting organic growth in the program. Really. So it, it shows, I think that there is value in what we can offer them as a platform to build a cloud on. >>Yeah. What's been interesting is there's there's growth and there's some transition as well. Right? So there's been traditional cloud providers. Who've built a cloud in their data center, some sovereign, some not. And then there's other partners that are adopting VCP P because of our SA. So we've either converted some technology from product into SA or we've built net new SA or we've acquired companies that have been SA only. And now we have a bigger portfolio that service providers, cloud providers, managed service providers are all interested in. So you get resellers channel partners. Who've historically been doing ELAs and reselling to end customers. They're transitioning their business into doing recurring revenue and the only game in town where you really wanna do recurring revenues, VCP P. So our ecosystem is both growing because our cloud providers with their data center are doing more with our customers. And then we're adding more managed service providers because of our SA portfolio. And that, that, that combo, that one, two punch is creating a much bigger VCP P ecosystem overall. >>Yeah. >>Impressive. >>Do you think we have a better idea of what sovereign cloud means? Yes. I think we do. >>It's not Royal. >>It's all about royalty, >>All royalty. What are some of the things Jeff, as we look on the horizon, obviously seven to 10,000 people here at, at VMwares where people really excited to be back. They want to hear it from VMware. They wanna hear from its partner ecosystem, the community. What are some of the things that you think are on the horizon where sovereign cloud is concerned that are really opportunities yeah. For businesses to get it right. >>Yeah. We're in the early days of this, I think there's still a whole bunch of rules, regulatory laws that have not been defined yet. So I think there's gonna be some more learning. There's gonna be some top down guidance like Gaia X in Europe. That's the way that they're defining who gets access and control over what data and what's in. And what's out of that. So we're gonna get more of these Gaia X type things happening around the world, and they're all gonna be slightly different. Everyone's gonna have to understand what they are, how to interpret and then build something around them. So we need to stay on top of that, myself and Jay, to make sure that we've got the right cloud providers in the right space to capitalize on that, build out the sovereign cloud program over time and make sure that what they're building to support aligns with these different requirements that are out there across different countries. So it's an evolving landscape. That's >>Yeah. And one of the things too, we're also doing from a product perspective to better enable partners to, to address these sovereign cloud workloads is where we have, we have gaps maybe in our portfolio is we're partner partnering with some of our ISVs, like a, Konic like a Forex vem. So we can give our partners object storage or ransomware protection to add on to their sovereign cloud service, all accessible through our cloud director consult. So we're, we're enhancing the program that way. And to Jeff's point earlier, we've got 20 partners today. We're hoping to double that by the end of our fiscal year and, and just take a very methodical approach to growth of the program. >>Sounds great guys, early innings though. Thank you so much for joining Dave and me talking about what software and cloud is describing it to us, and also talking about the difference between that data residency and all the, all of the challenges and the, in the landscape that customers are facing. They can go turn to VMware and its ecosystem for that help. We appreciate your insights and your time. Guys. Thank >>You >>For >>Having us. Our >>Pleasure. Appreciate it >>For our guests and Dave Nicholson. I'm Lisa Martin. You've been watching the cube. This is the end of day, two coverage of VMware Explorer, 2022. Have a great rest of your day. We'll see you tomorrow.

>>We're back at your storage service. Emil Stan is here. He's the chief commercial officer and chief marketing officer of open line. Thank you, Emil, for coming on the cube. Appreciate your time. >>Thank you, David. Nice. Uh, glad to be here. >>Yeah. So tell us about open line. You're a managed service provider. What's your focus? >>Yeah, we're actually a cloud managed service provider and I do put cloud in front of the managed services because it's not just only the scripts that we manage. We have to manage the clouds as well nowadays. And then unfortunately, everybody only thinks there's one cloud. But's always multiple layers in the cloud. So we have a lot of work in integrating, uh, it where a cloud manages provider in the Netherlands, focusing on, uh, companies who have a head office in the Netherlands, mainly in the, uh, healthcare local government, social housing logistics department. And then in the midsize companies between say 250 to 10,000 office employees. Uh, and that's what we do. We provide them with excellent cloud managed services, uh, as it should be >>Interesting, you know, lot early on in the cloud days, highly regulated industries like healthcare government were somewhat afraid of the cloud. So I'm sure that's one of the ways in which you provide value to your customers is helping them become cloud proficient. Maybe you could talk a little bit more about the value prop to customers. Why do they do business with you? >>Yeah, I think, uh, there are a number of reasons why they do business with us or choose to choose for our managed services provider. Tracy, of course, are looking for stability and continuity, uh, and, and from a cost perspective, predict predictable costs, but nowadays you also have a shortage in personnel and knowledge. So, and it's not always very easy for them to access, uh, those skill sets because most it, people just want to have, uh, a great variety in work, what they are doing, uh, towards, towards the local government, uh, healthcare, social housing. They actually, uh, a sector that, uh, that are really in between embracing the public cloud, but also have a lot of legacy and, and bringing together best of all, worlds is what we do. So we also bring them comfort. We do understand what legacy, uh, needs from a manager's perspective. We also know how to leverage the benefits in the public cloud. Uh, and, uh, I'd say from a marketing perspective, actually, we focus on using an ideal cloud, being a mix of traditional and future based cloud. >>Thank you. I, you know, I'd like to get your perspective on this idea of as a service and the, as a service economy that we often talk about on the cube. I mean, you work with a lot of different companies. We talked about some of the industries and, and increasingly it seems like organizations are focused more on outcomes, continuous value delivery via, you know, suites of services and, and they're leaning into platforms versus one off product offerings, you know, do you see that? How do you see your customers reacting to this as a service trend? >>Yeah. Uh, to be honest, sometimes it makes it more complex because services like, look at your Android or iPhone, you can buy apps, uh, and download apps the way you went to. So they have a lot of apps, but how do you integrate it into one excellent workflow, something that works for you, David or works for me? Uh, so the difficulty, some sometimes lies in, uh, the easy accessibility that you have to those solutions, but nobody takes into account that they're all part of a chain or workflow supply chain, uh, and, and, uh, they're being hyped as well. So what, we also have a lot of time in, in, in, in, in managing our customers, is that the tremendous feature push feature push that there is from technology providers, SaaS providers. Whereas if you provide 10 features, you only need one or two, uh, but the other eight are very distracting from your prime core business. Uh, so there's a natural way in that people are embracing, uh, SA solutions, embracing cloud solutions. Uh, but what's not taken into account as much is that we love to see it the way that you integrate all those solutions to it's something that's workable for the person that's actually using them. And it's seldomly that somebody is only using one solution. There's always a chain of solutions. Um, so yeah, there are a lot of opportunities, but also a lot of challenges for us, but also for our customers. >>Do you see that trend toward, as a service continuing, or do you actually see based on what you're just saying that pendulum, you know, swinging back and forth, somebody comes out with a new sort of feature product and that, you know, changes the dynamic or do you see as a service really having legs? >>Ah, that's very, very good question, David, because that's something that's keeps our busy all the time. We do see a trend in as a service looking at, uh, talk about pure later on. We also use pure as a service more or less. Yeah. And it really helps us. Uh, but you see, uh, um, that sometimes people make a step too, too fast, too quick, not well thought of, and then you see what they call sort of cloud repatriation, tend that people go back to what they're doing and then they stop innovating or stop leveraging. The possibilities are actually there. Uh, so from a consultancy guidance and architecture point of view, we try to help them as much possible to think in a SA thought, but just don't use the, cloud's just another data center. Eh, and so it's all about managing the maturity on our side, but on our customer side as well. >>So I'm interested in how you're sort of your philosophy and it relates, I think, in, in, in terms of how you work with pure, but how do you stay tightly in lockstep with, with your customers so that you don't over rotate so that you don't them to over rotate, but then you're not also, you don't wanna be too late to the game. How, how do you manage all that? >>Oh, there's, there's, there's a world of interactions between us and our customers. And so I think a well known, uh, uh, uh, thing that people, the most customer intimacy, that's very important for us to get to know our customers and get to predict which way they're moving. But the, the thing that we add to it is also the ecosystem intimacy. So no, the application and services landscape, our customers know the primary providers and work with them, uh, to, to, to create something that, that really fits the customers to just not look at from our own silo where a cloud managed service provider that we actually work in the ecosystem with, with, with, with the primary providers. And we have, I think where the average customers, I think we have, uh, uh, uh, in a month we have so much interactions on our operational level and technical levels, strategic level. >>We do bring together our customers also, and to jointly think about what we can do together, what we independently can never reach, but we also involve our customers in defining our own strategy. So we have something we call a customer involvement board. So we present a strategy and today, does it make sense? Eh, this is actually what you need also. So we take a lot of our efforts into our customers and we do also, uh, understand the significant moments of truth. We are now in this, in this broadcast, David there. So you can imagine that at this moment, not thinking go wrong. Uh, if, if, if the internet stops, we have a problem. And now, so we, we actually know that this broadcast is going on for our customers. And we manage that. It's always on, uh, uh, where in the other moments in the week, we might have a little less attention, but this moment we should be there in these moments of truth that we really embraced. We got them well described. Everybody working out line knows what the moment of truth is for our customers. Uh, uh, so we have a big logistics provider. For instance, you does not have to ask us to, uh, have, uh, a higher availability on black Friday or cyber Monday. We know that's the most important part in the year for him or her. Does it answer your question, David? >>Yes. We know as well. You know, when these big, the big game moments you have to be on your top, uh, top of your game. Yeah. Uh, you know, the other thing, a Emil about this as a service approach that I really like is, is it's a lot of it is consumption based and the data doesn't lie, you can see adoption, you know, D daily, weekly, monthly. And so I wonder how you're leveraging pure as a service specifically in what kind of patterns you're seeing in, in, in the adoption, >>Uh, pure as a service for our customers. It's mainly never visible. Uh, we provide storage services, provide storage solutions, storage job is part of a bigger thing of a server of application. Uh, so the real benefits to be honest of, of course, towards our customer, it's all flash, uh, uh, and they have the fast, fastest storage is available. But for ourself, we, uh, we use less resources to manage our storage. We have far more that we have a near to maintenance free storage solution now because we have it as a service and we work closely together with pure. Uh, so, uh, actually the way we treat our customers is the way pure treats us as well. And that's why there's a used click. So the real benefits, uh, uh, how we leverage is it normally we had a bunch of guys managing us storage. Now we only have one and knowing that's a shortage of it, personnel, the other persons can well be, uh, involved in other parts of our services or in other parts of an innovation. So, uh, that's simply great. >>You know, um, my takeaway Emil is that you've made infrastructure, at least, least the storage infrastructure, invisible to your customers, which is the way it should be. You didn't have to worry about it. And you've, you've also attacked the, the labor problem. You're not, you know, provisioning lungs anymore, or, you know, tuning the storage, you know, with, with arms and legs. So that's huge. So that gets me into the next topic, which is business transformation. That, that means that I can now start to attack the operational model. So I've got a different it model. Now I'm not managing infrastructure same way. So I have to shift those resources. And I'm presuming that it's a bus now becomes a business transformation discussion. How are you seeing your customers shift those resources and focus more on their business as a result of this sort of as a service trend? >>I think I do not know if they, they transform their business. Thanks to us. I think that they can more leverage their own business. They have less problems, less maintenance, et cetera, et cetera. But we also add new, uh, certainties to it, like, uh, uh, the, the latest service we we released was imutable storage being the first in the Netherlands offering this thanks to, uh, thanks to the pure technology, but for customers, it takes them to give them a good night rest because, you know, we have some, uh, geopolitical issues in the world. Uh, there's a lot of hacking. People have a lot of ransomware attacks and, and we just give them a good night rest. So from a business transformation, doesn't transform their business. I think that gives them a comfort in running your business, knowing that certain things are well arranged. You don't have to worry about that. We will do that. We'll take it out of your hands and you just go ahead and run your business. Um, so to me, it's not really transformation. It's just using the right opportunities at the right moment. >>The imutable piece is interesting because of course, but speaking of as a service, you know, anybody can go on the dark web and buy ransomware as a service. I mean, as it's, he was seeing the, as a service economy hit, hit everywhere, the good and the, and the not so good. Um, and so I presume that your customers are, are looking at, I imutability as another service capability of the service offering and really rethinking, maybe because of the recent, you know, ransomware attacks, rethinking how they, they approach, uh, business continuance, business resilience, disaster recovery. Do you see that? >>Yep, definitely. Definitely. I, not all of them yet. Imutable storage. So it's like an insurance as well. Yeah. Which you have when you have imutable storage and you have, you have a ransomware attack, at least if you part the data, which never, if data is corrupted, you cannot restore it. If your hardware is broken, you can order new hardware. Every data is corrupted. You cannot order new data. Now we got that safe and well. And so we offer them the possibility to, to do the forensics and free up their, uh, the data without a tremendous loss of time. Uh, but you also see that you raise the new, uh, how do you say, uh, the new baseline for other providers as well? Eh, so there's security of the corporate information security officer, the CIO, they're all fairly happy with that. And they, they, they raise the baseline for others as well. So they can look at other security topics and look from, say a security operation center that now we can really focus on our prime business risks, because from a technical perspective, we got it covered. How can we manage the business risk, uh, which is a combination of people, processes and technology. >>Right. Makes sense. Okay. I'll give you the last word. Uh, talk about your relationship with pure, where you wanna see that, that going in the future. >>Uh, I hope we've be working together for a long time. Uh, I, I ex experienced them very involved. Uh, it's not, we have done the sell and now it's all up to you now. We really closely working together. I know if I talk to my prime marketing, Marcel height is very happy and it looks a little more or less if we work with pure, like we're working with colleagues, not with a supplier, uh, and a customer, uh, and, uh, the whole pure concept is quite fascinating. Uh, I, uh, I had the opportunity to visit San Francisco head office, and they told me to fish in how they launched pure being, if you want to implement it, it had to be on one credit card. The, the, the menu had to be on one credit card, just a simple thought of put that as your big hair, audacious goal to make the simplest, uh, implementable storage available. But for, uh, it gives me the expectation that there will be a lot of more surprises with puring in near future. Uh, and for us as a provider, what we, uh, literally really look forward to is that, that for us, these new developments will not be new migrations. It will be a gradual growth of our services on storage services. Uh, so that's what I expect, and that was what I, and we look forward to. >>Yeah, that's great. Uh, thank you so much, Emil, for coming on the, the cube and, and sharing your thoughts and best of luck to you in the future. >>Thank you. >>You're welcome. Thanks for having me. You're very welcome. Okay. In a moment, I'll be back to give you some closing thoughts on at your storage service. You're watching the cube, the leader in high tech enterprise coverage.

>>When AWS introduced the modern cloud in 2006, many people didn't realize the impact that it would have on the industry, but some did see the future of an as a service economy coming. I mean, SAS offerings came out several years before. And the idea of applying some of these concepts to infrastructure and simplifying deployment and management, you know, kinda looked enticing to a lot of customers and a subscription model, or, but yet a consumption model was seen as a valuable proposition by many customers. Why not apply it to infrastructure? And why should the hyperscalers have all the fun welcome to at your storage service? My name is Dave ante. And as an analyst at the time, I was excited about the, as a service trend early on. And one of the companies that caught my attention back in the beginning of last decade was pure storage. >>Pure not only was delivering cloud- simplicity, but it's no forklift approach to infrastructure was ahead of its time. And that's why we're here today to dig into what's happening with the, as a service trends that we see popping up all over the world today, we're gonna dig into three sessions with noted experts in the field. First pre Darie is the general manager of the digital experience business unit at pure storage. He's gonna join us. And then we bring in Steve McDowell, Steve's a senior analyst for data and storage at more insights and strategy, a well known consultancy and analyst firm. And finally, we close with Amil sta Emil is the chief commercial officer and chief marketing officer at open line, open lines, a managed service provider. They serve the mid-market and Emil's got a very wide observation space. He's gonna share what he's seeing with customers. So sit back and enjoy the show. >>The cloud has popularized many useful concepts in the past decade, working backwards from the customer two pizza teams, a DevOps mindset, the shared responsibility model in security. And of course the shift from CapEx to OPEX and as a service consumption models. The last item is what we're here to talk about today. Pay for consumption is attractive because you're not over provisioning. At least not the way you used to you'd have to buy for peak capacity events, but there are always two sides to every story and well pay for use more closely ties. It consumption to business value procurement teams. Don't always love the uncertainty of the cloud bill each month, but consumption pricing. And as a service models are here to stay in software and hardware. Hello, I'm Dave ante and welcome to at your storage service made possible by pure storage. And with me is Pash DJI. Who's the general manager of the digital experience business unit at pure Pash. Welcome to the program. >>Thanks Dave. Thanks for having me. >>You bet. Okay. We've seen this shift to, as a service, the, as a service economy, subscription models, and this as a service movement have gained real momentum. It's it's clear over the past several years, what's driving this shift. Is it pressure from investors and technology companies that are chasing the all important ARR, their annual recurring revenue stream? Is it customer driven? Give us your insights. >>Well, look, um, I think we'll do some definitional stuff first. I think we often mix the definition of a subscription and a service, but, you know, subscription is, Hey, I can go for pay up front or pay as I go. Service is more about how do I not buy something just by the outcome. So, you know, the concept of delivering storage as a service means, what do you want in storage performance, capacity availability? Like that's what you want. Well, how do you get that without having to worry about the labor of planning capacity management, those labor elements are what's driving it. So I think in the world where you have to do more with less and in a world where security becomes increasingly important, where standardization will allow you to secure your landscape against ransomware and those types of things, those trends are driving the ation of storage and the only way to deliver that is storage as a service. >>So that's, that's good. You maybe thinking about it differently than some of the other companies that I talked to, but so you, you, you've made inroads here pretty big inroads actually, and changed the thinking in enterprise data storage with a huge emphasis on simplicity. That's really pures rayon Detra. How does storage as a service fit into your innovation agenda overall? >>Well, our innovation agenda started, as you mentioned with the simplicity, you know, a decade ago with the evergreen architecture, that architecture was beyond the box. How do you go ahead and say, I can improve performance or capacity as I need it? Well, that's a foundational element to deliver a service because once you have that technology, you can say, oh, you know what? You've subscribed to this performance level. You want to raise your performance level and yes, that'll be a higher dollar per gig or dollar per terabyte. But how do you do that without a data migration? How do you do that with a non disruptive service change? How do you do that with a delivery via a software update, those elements of non disruptive updates. When you think SAS, Salesforce, you don't know when Salesforce doesn't update, you don't know when they're increasing something, adding a new capability just shows up. It's not a disruptive event. So to drive that standardization and sation and service delivery, you need to keep that simplicity of delivery first and foremost, and you can't allow, like, if the goal was, I want to change from this service tier to that service tier and a person needed to show up and do a day data migration, that's kind of useless. You've broken the experience of flexibility for a customer. >>Okay. So I like the Salesforce analogy, but I wanna jump out, do a little side for a second. So I I've gotta, I've gotta make some commitment to pure, right. Some baseline commitment. And if I do, then I can dial up and pay for what I use and I can dial it down. Correct? Correct. Okay. I can't do that with Salesforce. <laugh> right. I could dial up, but then I'm stuck with those licenses. So you have a better model in Salesforce. I would argue. Okay. Yeah, >>I would, I would agree with that. >>Okay. So, and I gotta pay for everything up front anyway. Um, let's go back. I was kind of pushing at you a little bit at my upfront, you know, about, you know, the ARR model, the, the all important, you know, financial metric, but let's talk from the customers standpoint. What are the benefits of consuming storage as a service from your customer's perspective? >>Well, one is when you start your storage journey, do you really know what you need? And I would argue most of the time people are guessing, right? It's like, well, I think I need this. This is the performance I think I need. Or this is the capacity I think I need. And, you know, with the scientific method, you actually deploy something and you're like, do I need more? Do I need less? You find out as you're deploying. So in a storage as a service world, when you have the ability to move up performance levels or move out capacity levels, and you have that flexibility, then you have the ability to just to meet demand as you deploy. And that's the most important element of meeting business needs today. The applications you deploy are not in your control when you're providing storage to your end consumers. >>Yeah. They're gonna want different levels of storage. They're gonna want different performance thresholds. That's kind of a pay, you know, pay for performance type culture, right? You can use HR analogies for it. You pay for performance. You want top talent, you pay for it. You want top storage performance, you pay for it. Um, you don't, you can pay less and you can actually get lower performance, tiers, not everything is a tier one application. And you need the ability to deploy it. But when you start, how do you know the way your end customers are gonna be consuming? Or do you need a dictated upfront? Cause that's infrastructure dictating business inflexibility, and you never want to be in that position. >>I, I got another analogy for you. It's like, you know, we do a lot of hosting at our home and you know, like Thanksgiving, right? And you go to the liquor store and say, okay, what should I get? Should we get red wine? We gotta go white wine. We gotta get some beer. Should I get bubbles? Yeah, I get some bubbles. Cause you don't know what people are gonna have. And so you over provision everything <laugh> and then there's a run on bubbles and you're like, ah, we run outta bubbles. So you just over buy, but there's a liquor store that actually will take it back. So I gotta do business with those guys every time. Cuz it's way more flexible. I can dial up capacity or can dial up performance and dial it back down if I don't use it >>Or you or you're gonna be drinking a lot more the next few weeks. >>Yeah, exactly. Which is the last thing you want. Okay. So let's talk about how pure kind of meets this as a service demand. You've touched upon your, your differentiators from others in the market. Um, you know, love to hear about the momentum. What, what are you seeing out there? >>Yeah. Look, our business is growing well, largely built on, you know, what customers need. Um, specifically where the market is at today is there's a set of folks that are interested in the financial transformation of CapEx to OPEX, where like that definitely exists in the industry around how do I get a pay use model? The next kind of more advanced customer is interested in how do I go ahead and remove labor to deliver storage? And a service gets you there on top of a subscription. The most sophisticated customer says, how do I separate storage production with consumption and production of storage. Being a storage producer should be about standardization. So I could do policy based management. Why is that important? You know, coming back to some of the things I said earlier in the world where ransomware attacks are common, you need the standardized security policies. >>Linux has new vulnerabilities every, every other day, like find 2, 2, 3 critical vulnerabilities a week. How do you stay on top of it? The complexity of staying on top of it should be, look, let's standardize and make it a vendor problem. And assume the vendor's gonna deliver this to me. So that standardization allows you to have business policies that allow you to stay current and modern. I would argue in, you know, the traditional storage and appliance world, you buy something and the day a, the day after you buy it, it's worthless. It's like driving a car off a lot, right? The very next day, the car's not worth what it was when you bought it. Storage is the same way. So how do you ensure that your storage stays current? How do you ensure that it gets like a fine line that gets better, better with age? Well, if you're not buying storage and you're buying a performance SLA, it's up to the vendor to meet that SLA. So it actually never gets worse over time. This is the way you modernize technology and avoid technology debt as a customer. >>Yeah. I mean, just even though words you're using in the way you're thinking about this precaution, I think are, are, are different. Uh, and I love the concept of essentially taking my labor cost and transferring them to pures R and D I mean, that's essentially what you're talking about here. Um, so let's, let's, let's stick with the, the, the tech for a minute. What do you see as new or emerging technologies that are helping accelerate this shift toward the, as a service economy? >>Well, the first thing is I always tell people, you can't deliver a service without monitoring, because if you can't monitor something, how you're gonna know what your, whether you're meeting your service level obligation, right? So everything starts with data monitoring. The next step layering on the technology. Differentiation is if you need to deliver a service level, OB obligation on top of that data monitoring, you need the ability to flexibly, meet whatever performance obligations you have in a tight time window. So supply chain and being able to deliver anywhere becomes important. So if you use the analogy today of how Tesla works or a IOT system works, you have a SaaS management that actually provides instructions that push pushes those instructions and policies to the edge. In Tesla's case, that happens to be the car it'll push software updates to the car. It'll push new map updates to the car, but the car is running independently. >>It's not like if the car becomes disconnected from the internet, it's gonna crash and drive you off the road in the same way. What if you think about storage as something that needs to be wherever your application is? So people think about cloud as a destination. I think that's a fallacy. You have to think about the world in the world in the view of an application, an application needs data, and that data needs to sit in storage wherever that application sits. So for us, the storage system is just an edge device. It can be sitting in your data center, it can be sitting in a Equinix. It can be sitting in hosted, an MSP can run. It can, can even be sitting in the public cloud, but how do you have central monitoring and central management where you can push policies to update all those devices? >>Very similar to an I IOT system. So the technology advantage of doing that means that you can operate anywhere and ensure you have a consistent set of policies, a consistent set of protection, a consistent set of, you know, prevention against ransomware attack, regardless of your application, regardless of, uh, you know, where it sits, regardless of what content in you're on that approach is very similar to the way the T industry has been updating and monitoring edge devices, nest, thermostats, you know, Tesla cars, those types of things. That's the thinking that needs to come to. And that's the foundation on which we built PI as a service. >>So that implies, or at least I infer that you've obviously got control of the experience on Preem, but you're extending that, uh, into AWS, Google Azure, which suggests to me that you have to hide the underlying complexity of the primitives and APIs in that world. And then eventually, actually today, cuz you're treating everything like the edge out to the edge, you know, maybe, maybe mini pure at some point in time. But so I call that super cloud that abstraction layer that floats above all the clouds on-prem and adds that layer of value. And is this singular experience? What you're talking about pushing, you know, policy throughout, is that the right way to think about it and how does this impact the ability to deliver true storage as a service? >>Oh, uh, that's absolutely the right way of thinking about it. The things that you think about from a, an abstraction kind of fall in three buckets, first, you need management. So how do you ensure a consistent management experience creating volumes, deleting volumes, creating buckets, creating files, creating directories, like management of objects and create a consistent API across the entire landscape. The second one is monitoring, how do you measure utilization and performance obligations or capacity obligations or uh, you know, policy violations, wherever you're at. And then the third one is more of a business one, which is procurement because you can't do it independent of procurement. Meaning what happens when you run out, you need to increase your reserve commits. Do you want to go on demand? How do you integrate it into company's procurement models, such that you can say, I can use what I need and any, it's not like every change order is a request of procurement. That's gonna break an as a service delivery model. So to get embedded in a customer's landscape where they don't have to worry about storage, you have to provide that consistency on management, monitoring and procurement across the tech. And yes, this is deep technology problems, whether it's running our storage on AWS or Azure or running it on prem or, you know, at some point in the future, maybe even, um, you know, pure mini at the edge. Right. <laugh> so, you know, tho all of those things are tied to our pure, a service delivery. >>Yeah, technically non-trivial but uh, Hey, you guys are on it. Well, we gotta leave it there. Pash. Thank you. Great stuff. Really appreciate your time. >>All right. Thanks for having me, man. >>You're very welcome. Okay. In a moment, Steve McDowell from more insights and strategies, it's gonna give us the analyst perspective on, as a service, you're watching the cube, the leader in high tech enterprise coverage. >>Why are customers making the change to pure as a service >>Other vendors, offering flexible consumption models will promise you the world on the surface. It's just what you need. But then you notice the asterisk that dreaded fine print. That turns just what you need into long-term commitments, disruptive upgrades and unpredictable costs, pure storage, launched pure as a service to provide the flexibility to respond to your ever changing needs. With clear per unit costs, no large upfront purchases and no asterisks. A usage based model should be simple, innovative, and adapt with the changing market. Unlike other vendors, pure is offering exactly that with options, for service tiers and short term contracts in a single unified subscription that allows you to improve your discounts over time. Pure makes sure you can grow and upgrade without ever taking your environment offline and without the constant worry of hidden costs with complete billing, transparency, unlike any other, you only pay for what you use and pure one helps track and predict demand from day to day, making sure you never outgrow your storage. So why are customers making the change to pure as a service convenient solutions with unlimited potential without the dreaded fine print? It's as simple as that, >>We're back with Steve McDowell, the principal analyst for data and storage at more insights and strategy. Hey Steve, great to have you on, tell us a little bit about yourself. You got a really interesting background and kind of a blend of engineering and strategy and what's your research focus? >>Yeah, so my research, my focus area is data and storage and all the things around that, right? Whether it's OnPrim or cloud or, or, or, you know, software as a service. Uh, my background, as you said, is a blend, right? I grew up as an engineer. I started off as an OS developer at IBM. Uh, came up through the ranks and, and shifted over into corporate strategy and product marketing and product management. Uh, and I've been doing, uh, working as an industry analyst now for about five years, more insights and strategy. >>Steve, how do you see this playing out in the next three to five years? I mean, cloud got it all started. It's gonna snowballing, you know, however you look at it, percent of spending on storage that you think is gonna land in as a service. How, how do you see the evolution here? >>I think it buyers are looking at as a service, a consumption based is, is, uh, uh, you know, a natural model. It extends the data center, brings all of the flexibility, all of the goodness that I get from public cloud, but without all of the downside and uncertainty around cost and security and things like that, right. That also come with a public cloud and it's delivered by technology providers that I trust and that I know, and that I've worked with, you know, for, in some cases, decades. So I don't know that we have hard data on how much, uh, adoption there is of the model, but we do know that it's trending up, uh, you know, and every infrastructure provider at this point has some flavor of offering in the space. So it's, it's clearly popular with CIOs and, and it practitioners alike. >>So Steve organizations are at a they're different levels of maturity in their, their transformation journeys. And of course, as a result, they're gonna have different storage needs that are aligned with their bottom line business objectives. From an it buyer perspective, you may have data on this, even if it's anecdotal, where does storage as a service actually fit in and can it be a growth lever >>Can absolutely be, uh, a growth leader. Uh, it, it gives me the flexibility as, as an it architect to scale my business over time, without worrying about how much money I have to invest in, in storage hardware. Right? So I, I get kind of, again, that cloudlike flexibility in terms of procurement and deployment. Uh, but it gives me that control by oftentimes being on site within my permit. And I manage it like a storage array that I own. Uh, so you know, it, it's, it's beautiful for, for organizations that are scaling and, and it's equally nice for organizations that just wanna manage and control cost over time. Um, so it's, it's a model that makes a lot of sense and fits and, and certainly growing in adoption and popularity. >>How about from a technology vendor perspective you've worked for in the, in the tech industry mm-hmm <affirmative> for, for companies? What do you think is gonna define the winners and losers in this space? If you were running strategy for, uh, storage company, what would you say? >>I, I think the days of, of a storage administrator managing, you know, rate levels and recovering and things of that sort are over, right, what would, what these organizations like pure delivering, but they're offerings is, is simplicity. It's a push button approach to deploying storage to the applications and workloads that need it, right. It becomes storage as a utility. So it's not just the, you know, the consumption based economic model of, of, uh, as a service. Uh, it, it's also the manageability that comes with that, or the flexibility of management that comes with that. I can push a button, deploy bites to, to, uh, you know, a workload that needs it. Um, and it just becomes very simple, right. For the storage administrator in a way that, you know, kind of old school OnPrim storage can't really deliver. >>You know, I wanna, I wanna ask you, I mean, I've been thinking about this because again, a lot of companies are, are, you know, moving, hopping on the, as a service bandwagon, I feel like, okay, in and of itself, that's not where the innovation lives, the innovation is gonna come from making that singular experience from on-prem to the clouds across clouds, maybe eventually out to the edge. Um, do you, do you, where do you see the innovation in as a service? >>Well, there there's two levels of innovation, right? One, one is business model innovation, right? I, I now have an organizational flexibility to build the infrastructure, to support my digital transformation efforts. Um, but on the product side and the offering side, it really is, as you said, it's about the integration of experience. Every enterprise today touches a cloud in some way, shape or form, right. I have data spread, not just in my data center, but at the edge, uh, oftentimes in a public cloud, maybe a private cloud, I don't know where my data is and it really lands on the storage providers to help me manage that and deliver that, uh, uh, manageability experience, uh, to, to the it administrators. So when I look at innovation in this space, you know, it's not just a storage array and rack that I'm leasing, right? This is not another lease model. It's really fully integrated, you know, end to end management of my data and, and, you know, and all of the things around that. >>Yeah. So you, to your point about a lease model is if you're doing a lease, you know, yeah. You can shift CapEx to OPEX, but you're still committed to, to, you have to over provision, whereas here, and I wanted to ask you about that. It's, it's, it's, it's an interesting model, right? Cuz you gotta read the fine print. Of course the fine print says you gotta commit to some level typically. And then if, you know, if you go over you, you charge for what you use and you can scale that back down and that's, that's gotta be very attractive for folks. I, I wonder if you will ever see like true cloud-like consumption pricing, that is two edges to it. Right. You see consumption based pricing in some of the software models and you know yeah. People like it, the lines of business maybe cuz they pay in by the drink, but then procurement hates it cuz they don't have predictability. How do you see the pricing models? Do you see that maturing or do you think we're sort of locked in on, on where we're at? >>No, I, I do. I do see that maturing. Right? And, and when you work with a company like pure to understand their consumption based and as a service offerings, uh, it, it really is sitting down and understanding where your data needs are going to scale, right? You, you buy in at a certain level, uh, you have capacity planning. You can expand if you need to, you can shrink if you need to. So it really does put more control in the hands of the it buyer than uh, well certainly then traditional CapEx based on-prem but also more control than you would get, you know, working with an Amazon or an Azure. >>Okay. Thanks Steve. We'll leave it there for now. I'd love to have you back. Keep it right there at your storage service continues in a moment. >>Some things are meant to last your storage should be one of them say hello to the evergreen storage program, say goodbye to refreshes and rebates. Forget planned downtime, performance impact and data migrations. Forget forklift upgrades. Evergreen storage starts with your agile storage architecture and covers the entire life cycle of the array from first purchase to ongoing use. And whenever it's time to modernize and grow, your satisfaction is covered with an evergreen subscription. You can get a full refund within 30 days for any reason, >>Our right size guarantee lets you buy just the storage you need never too much. Never not enough. Your array software is all inclusive. Even future releases and features maintenance and support costs remain constant throughout the life of your array. Proactive expert support is a true white glove experience. Evergreen maintenance ensures availability of any replacement components. Meet the demands of your business and protect your investment. Evergreen gold includes controller upgrades every three years. And if something unplanned comes up, evergreen gold provides upgrade flex the leading anytime upgrade feature to upgrade controllers whenever you need it. As you expand evergreen gold provides credits to consolidate storage with denser more modern flash. Evergreen is your subscription to continuous innovation for storage that lasts 10 years or more. Some things are meant to last make your storage. One of them >>We're back at your storage service. Emil Stan is here. He's the chief commercial officer and chief marketing officer of open line. Thank you Emil for coming on the cube. Appreciate your time. >>Thank you, David. Nice. Uh, glad to be here. >>Yes. Yeah. So tell us about open line. You're a managed service provider. What's your focus? >>Yeah, we're actually a cloud managed service provider and I do put cloud in front of the managed services because it's not just only the spheres that we manage. We have to manage the clouds as well nowadays. And then unfortunately, everybody only thinks there's one cloud, but it's always multiple layers in the cloud. So we have a lot of work in integrating it. We're a cloud manages provider in the Netherlands, focusing on, uh, companies who have head office in the Netherlands, mainly in the, uh, healthcare local government, social housing logistics department. And then in the midst size companies between say 250 to 10,000 office employees. Uh, and that's what we do. We provide 'em with excellent cloud managed services, uh, as it should be >>Interesting, you know, a lot early on in the cloud days, highly regulated industries like healthcare government were somewhat afraid of the cloud. So I'm sure that's one of the ways in which you provide value to your customers is helping them become cloud proficient. Maybe you could talk a little bit more about the value prop to customers. Why do they do business with you? >>And I think, uh, there are a number of reasons why they do business with us or choose to choose for our manage services provider that first of course are looking for stability and continuity. Uh, and, and from a cost perspective, predict predictable costs. But nowadays you also have a shortage in personnel and knowledge. So, and it's not always very easy for them to access, uh, those skill sets because most it, people just want to have, uh, a great variety in work, what they are doing, uh, towards, towards the local government, uh, healthcare, social housing. They actually, uh, a sector that, uh, that are really in between embracing the public cloud, but also have a lot of legacy and, and bringing together best of all, worlds is what we do. So we also bring them comfort. We do understand what legacy, uh, needs from a manager's perspective. We also know how to leverage the benefits in the public cloud. Uh, and, uh, I'd say from a marketing perspective, actually we focus on using an ideal cloud, being a mix of traditional and future based cloud. >>Thank you. I, you know, I'd like to get your perspective on this idea of as a service and the, as a service economy that we often talk about on the cube. I mean, you work with a lot of different companies. We talked about some of the industries and, and increasingly it seems like organizations are focused more on outcomes, continuous value delivery via, you know, suites of services and, and they're leaning into platforms versus one off product offerings, you know, do you see that? How do you see your customers reacting to this as a service trend? >>Yeah. Uh, to be honest, sometimes it makes it more complex because services like, look at your Android or iPhone, you can buy apps, uh, and download apps the way you want to. So they have a lot of apps about how do you integrate it into one excellent workflow, something that works for you, David or works for me. Uh, so the difficulty, some sometimes lies in, uh, the easy accessibility that you have to those solutions, but nobody takes into account that they're all part of a chain, a workflow supply chain, uh, and, and, uh, they're being hyped as well. So what we also have a lot of time in, in, in, in managing our customers is that the tremendous feature push feature push that there is from technology providers, SaaS providers. Whereas if you provide 10 features, you only need one or two, uh, but the other eight are very distracting from your prime core business. Uh, so there's a natural way in that people are embracing, uh, SA solutions, embracing cloud solutions. Uh, but what's not taken into account as much is that we love to see it is the way that you integrate all those solutions toward something that's workable for the person that's actually using them. And it's seldomly that somebody is only using one solution. There's always a chain of solutions. Um, so yeah, there are a lot of opportunities, but also a lot of challenges for us, but also for our customers, >>You see that trend toward, as a service continuing, or do you actually see based on what you're just saying that pendulum, you know, swinging back and forth, somebody comes out with a new sort of feature product and that, you know, changes the dynamic or do you see as a service really having legs? >>Ah, I, I think that's very, very good question, David, because that's something that's keeping our busy all the time. We do see a trend in a service looking at, uh, talk about pure later on. We also use pure as a service more or less. Yeah. And that really helps us. Uh, but you see, uh, um, that sometimes people make a step too, too fast, too quick, not well thought of, and then you see what they call sort of cloud repatriation, tend that people go back to what they're doing and then they stop innovating or stop leveraging. The possibilities are actually there. Uh, so from our consultancy, our guidance and architecture point of view, we try to help them as much as possible to think in a SA thought, but just don't use the, cloud's just another data center. Uh, and so it's all about managing the maturity on our side, but on our customer side as well. >>So I'm interested in how your sort of your philosophy and, and as relates, I think in, in, in terms of how you work with pure, but how do you stay tightly in lockstep with your customers so that you don't over rotate so that you don't and send them to over rotate, but then you're not also, you don't wanna be too late to the game. How, how do you manage all that? >>Oh, there's, there's, there's a world of interactions between us and our customers. And so I think a well known, uh, uh, thing that people is customer intimacy. That's very important for us to get to know our customers and get to predict which way they're moving. But the, the thing that we add to it is also the ecosystem intimacy. So no, the application and services landscape, our customers know the primary providers and work with them, uh, to, to, to create something that, that really fits the customers. They just not looked at from our own silo where a cloud managed service provider that we actually work in the ecosystem with, with, with, with the primary providers. And we have, I think with the average customers, I think we have, uh, uh, in a month we have so much interactions on our operational level and technical levels, strategic level. >>We do bring together our customers also, and to jointly think about what we can do together, what we independently can never reach. Uh, but we also involve our customers in, uh, defining our own strategy. So we have something we call a customer involvement board. So we present a strategy and say, does it make sense? Eh, this is actually what you need also. So we take a lot of our efforts into our customers and we do also, uh, understand the significant moments of truth. We are now in this, in this broadcast, David there. So you can imagine that at this moment, not thinking go wrong. Yeah. If, if, if the internet stops that we have a problem. And now, so we, we actually know that this broadcast is going on for our customers and we manage that. It's always on, uh, uh, where in the other moments in the week, we might have a little less attention, but this moment we should be there. And these moments of truth that we really embrace, we got them well described. Everybody working out line knows what the moment of truth is for our customers. Uh, uh, so we have a big logistics provider. For instance, you does not have to ask us to, uh, have, uh, a higher availability on black Friday or cyber Monday. We know that's the most important part in the year for him or her. Does it answer your question, David? >>Yes. We know as well. You know, when these big, the big game moments you have to be on your top, uh, top of your game, uh, you know, the other thing Emil about this as a service approach that I really like is, is it's a lot of it is consumption based and the data doesn't lie, you can see adoption, you know, daily, weekly, monthly. And so I wonder how you're leveraging pure as a service specifically in what kind of patterns you're seeing in, in, in the adoption. >>Uh, yeah, pure as a service for our customers is mainly never visible. Uh, we provide storage services to provide storage solutions, storage over is part of a bigger thing of a server of application. Uh, so the real benefits, to be honest, of course, towards our customer, it's all flash, uh, uh, and they have the fastest, fastest storage is available. But for ourself, we, uh, we use less resources to manage our storage. We have far more that we have a near to maintenance free storage solution now because we have it as a service and we work closely together with pure. Uh, so, uh, actually the way we treat our customers is that way pure treats us as well. And that's why there's a used click. So the real benefits, uh, uh, how we leverage is it normally we had a bunch of guys managing our storage. Now we only have one and knowing that's a shortage of it, personnel, the other persons can well be, uh, involved in other parts of our services or in other parts of an innovation. So, uh, that's simply great. >>You know, um, my takeaway the meal is that you've made infrastructure, at least, least the storage infrastructure, invisible to your customers, which is the way it should be. You didn't have to worry about it. And you've, you've also attacked the, the labor problem. You're not, you know, provisioning lungs anymore, or, you know, tuning the storage, you know, with, with arms and legs. So that's huge. So that gets me into the next topic, which is business transformation. That, that means that I can now start to attack the operational model. So I've got a different it model. Now I'm not managing infrastructure same way. So I have to shift those resources. And I'm presuming that it's a bus now becomes a business transformation discussion. How are you seeing your customers shift those resources and focus more on their business as a result of this sort of as a service trend? >>I think I do not know if they, they transform their business. Thanks to us. I think that they can more leverage their own business. They have less problems, less maintenance, et cetera, cetera, but we also add new, uh, certainties to it, like, uh, uh, the, the latest service we we released was imutable storage being the first in the Netherlands offering this thanks to, uh, thanks to the pure technology, but for customers, it takes them to give them a good night rest because, you know, we have some, uh, geopolitical issues in the world. Uh, there's a lot of hacking. People have a lot of ransomware attacks and, and we just give them a good night rest. So from a business transformation, does it transform their business? I think that gives them a comfort in running your business, knowing that certain things are well arranged. You don't have to worry about that. We will do that. We'll take it out of your hands and you just go ahead and run your business. Um, so to me, it's not really a transformation is just using the right opportunities at the right moment. >>The imutable piece is interesting because, because, but speaking of as a service, you know, anybody can go on the dark web and buy ransomware as a service. I mean, as it's seeing the, as a service economy hit, hit everywhere, the good and the, and the not so good. Um, and so I presume that your customers are, are looking at, I imutability as another service capability of the service offering and really rethinking, maybe because of the recent, you know, ransomware attacks, rethinking how they, they approach, uh, business continuance, business resilience, disaster recovery. Do you see that? >>Yep, definitely. Definitely. I tell not all of them yet. Imutable storage. So it's like an insurance as well, which you have when you have imutable storage and you have been, you have a ransomware attack at least have you part of data, which never, if data is corrupted, you cannot restore it. If your hardware is broken, you can order new hardware. Every data is corrupted. You cannot order new data. Now we got that safe and well. And so we offer them the possibility to, to do the forensics and free up their, uh, the data without tremendous loss of time. Uh, but you also see that you raise the new, uh, how do you say, uh, the new baseline for other providers as well? Eh, so there's security of the corporate information security officer, the CIO, they're all very happy with that. And they, they, they raise the baseline for us as well. So they can look at other security topics and look from say, security operation center. Cuz now we can really focus on our prime business risks because from a technical perspective, we got it covered. How can we manage the business risk, uh, which is a combination of people, processes and technology. >>Right. Makes sense. Okay. I'll give you the last word. Uh, talk about your relationship with pure, where you wanna see that that going in the future. >>Uh, I hope we've be working together for a long time. Uh, I, I ex experienced them very involved. Uh, it's not, we have done the sell and now it's all up to you now. We were closely working together. I know if I talk to my prime architect, Marcel height is very happy and it looks a little more or less if we work with pure, like we're working with colleagues, not with a supplier and a customer, uh, and uh, the whole pure concept is fascinating. Uh, I, uh, I had the opportunity to visit San Francisco head office and they told me to fish in how they launched, uh, pure being, if you want to implement it, it had to be on one credit card. The, the, the menu had to be on one credit card. Just a simple thought of put that as your big area, audacious goal to make the simplest, uh, implementable storage available. But for us, uh, it gives me the expectation that there will be a lot of more surprises with pur in the near future. Uh, and for us as a provider, what we, uh, literally really look forward to is that, that for us, these new developments will not be new migrations. It will be a gradual growth of our services or storage services. Uh, so that's what I expect. And that was what I, and we look forward to. >>Yeah, that's great. Uh, thank you so much, Emil, for coming on the, the cube and, and sharing your thoughts and best of luck to you in the future. >>Thank you. You're welcome. Thanks for having me. >>You're very welcome. Okay. In a moment, I'll be back to give you some closing thoughts on at your storage service. You're watching the cube, the leader in high tech enterprise coverage. >>Welcome to evergreen, a place where organizations grow and thrive rooted in the modern data experience in evergreen people find a seamless, simple way to leverage data through market leading sustainable technology, financial flexibility, and effortless management, allowing everyone to innovate with data confidently. Welcome to pure storage. >>Now, if you're interested in hearing more about Pure's growing portfolio of technology and services and how they're transforming the enterprise data experience, be sure to register for pure accelerate tech Fest. 22 digital event is also taking place as an in-person event. On June 8th, you can register at pure storage.com/accelerate, pure storage.com/accelerate. You're watching the cue, the leader in enterprise and emerging tech coverage.

(gentle music) >> High profile cyber attacks like the SolarWinds hack, the JBS meat and the Florida municipality breach, have heightened awareness of how exposed, critical infrastructure has become. Because the pandemic has shifted employees to remote modes of work, hackers now have a much easier target to fish for credentials and exploit less secure home networks. Take the recent Log4j vulnerability, that's yet another example, of how hackers can take advantage of weak links in the chain. Now data storage companies have an important role to play in fighting cyber crime. Ultimately, they provide the equivalent of a bank vault if you will, and are responsible for storing and protecting the data that cyber criminals are targeting to steal or encrypt, in an effort to hold companies hostage, in a ransomware attack. Now in an effort to help customers understand how to protect themselves from such vulnerabilities, and how one storage company is addressing these challenges, the Cube is hosting this special presentation InfiniGuard Cyber Resilience: New Cybercrime Solutions. And we're going to speak with Eric Herzog, who's the Chief Marketing Officer of Infinidat, and then we'll bring in Stan Wysocki who is the president of Mark III Systems who is either an expert in IT infrastructure and artificial intelligence. First, let me welcome Eric Herzog back to the Cube, hello, Eric. >> Great, Dave, thank you very much, always love talking to you and the Cube, about leading edge technology solutions for end users. >> Alright let's do it. So, first we want to address the transformation and big business progress of Infinidat. New CEO, he's injected new management, new head of marketing obviously, Phil Bullinger is really been focused on accelerating the company's original vision, and doing so, Eric, in the typically unconventional style of Infinidat, you just put out a press release, capping 2021, can you set the stage for us, and give us the business update? >> Sure, so of course we summarized our 2021 results. What a very, very strong year. What a very, very strong year. We increased our bookings over 40% year to year. Even in Q4, we increased our bookings over 68%. And over 25% of the fortune 50 use an Infinidat solution, either our InfiniBox, or InfiniBox SSA, all flash array, or our Infiniguard, which is the focus of the launch we're doing today, on February 9th. >> Yeah, so I always said that Infinidat is one of the best kept secrets in the storage business. So let's talk about that hard news, what you launched on February 9th, and why it's important. >> Well, what we've done is we've got a high end enterprise purpose-built backup appliance, the InfiniGuard. We made some substantial advances in that. The key is focused on cyber resilience with what we call our infinisafe technology. Infinisafe incorporates a number of subsets, of cyber resilience from immutable snapshots, to logical air gapping, to fenced isolated networks, to almost instantaneous recovery for your backup data sets. In addition, we also dramatically improved the performance of the backup and recovery, which means, for example, if a backup window was taking three hours, now the backup window on that primary backup dataset could take only an hour and a half, which of course, as we all know backup dramatically impacts the performance of your primary applications, your primary servers, and your primary storage. So we've done both the cyber resilience aspect and then, on modern data protection, making sure that the backup and recovery are faster, for a traditional backup workload. >> So tell us a little bit more about Infinisafe, and specifically, Eric I'm interested in how it's different from other solutions, don't make me a liar, I had said, you guys always kind of take nonconventional approaches so tell us, add a little color to Infinisafe and how is it really unique from competitors? >> Sure, well Infinisafe incorporates as I mentioned, several different aspects. First of all, the immutable snapshots. So immutable snapshots can not be deleted, they cannot be altered, you cannot accelerate the rate, you can set the rate of immutable stuff, do I want to do it once a day? Do I want to do it twice a day? And obviously if a hacker could get in, you could accelerate that. Our immutable snaps are physically separated from the management schema. So the inside of an Infiniguard, we have what we call a data dedupe appliance, and that data dedupe engine, it goes ahead and it applies data reduction technology, to that back up data set. But we've divorced the immutable snapshots from the management of what we now call a DDE. So the DDE has kind of access of giving you that gap, that logical gap between the management schema of a DDE, and of course the immutable snapshot. We also combine that with this air gap technology, you've got the immutability and the air gap, which is local in that instance, but we also can do it remotely. So we can replicate from one Infiniguard in data center A, to a different Infiniguard in data center B. You then can configure that backup data set with the same immutable snapshot, and the same length, one day, half a day, six hours, whatever you choose, and then of course it'll have that same capability. The third thing we've done is very unique. We have a fenced isolated network to perform forensics. So, if the Cube has a cyber or malware attack, you need to make sure that once you've cleaned it up, off the primary storage, the primary servers, that you recover, a known good data set. So we set up this isolated fence network in which to perform that forensic analysis, to give you the appropriate good recover point. However, unlike many of our competitors, we can do it with a single InfiniBox. Some of our competitors, right on their websites say, you need two of their purpose-built backup appliances, to do cyber resilience. Meaning, twice the CapEx and twice the OpEx, which we can do with a single Infiniguard solution. And then lastly is our near instantaneous recovery. As you know, we're recovering backup data sets. We can make between 15 and 30 minutes time, the backup data set fully accessible to the backup admin or the storage admin to use their Commvault, their Veeam, their Veritas, their IBM Spectrum Protect, or whatever their backup software is, to do recovery from the InfiniGuard box, back to the primary storage using of course the backup software that they created the original dataset with. That is very unique. When you look out in the industry and look at, whether it be purpose-built backup competitors, or whether you look at primary storage competitors, almost no one talks about the speed of their recovery, and the one or two that do, talk about recovering the data set. We recover the entire environment. We are ready to go, and the backup admin, if they were, for example, Commvault, Veeam or Veritas, they could immediately start the backup, as soon as we did our recovery, which again, takes between 15 and 30 minutes, independent of the data set size. That could be 50 terabytes, it could be a petabyte, it could be two petabytes. And even two petabytes of data can be available in 15 to 30 minutes. And then of course, the backup admin can restore from that backup dataset. Very powerful and very unique in those aspects. >> Whilst the reason why this is so important is like I said, it's like the bank vault, because hackers are going to go after that backup corpus that's where the gold is, that's where all the data is. So this all really sounds good. But there's more than Infinisafe in this launch. What else should we know? >> Well, the other thing we've done is dramatically improved the performance of the purpose-built backup plants at the core. So for example, the last time we publicly announced our numbers, we were at 74 terabytes an hour, now we're 180 terabytes an hour. So of course, as we all know, when you do a backup, it impacts the performance of the primary applications, the primary servers and the primary storage. So if that backup window was taking three hours, now that we've more than doubled the performance, you could be up to 50% better. So a three hour backup window, if that's what the dataset took to be backed up, now we can get that down to an hour and a half or even faster. So that of course minimizes the impact on primary storage, primary applications, and of course your primary storage, making it much, much more efficient, from a backup perspective, and of course less impact on the primary applications, the primary servers, and primary storage. >> So I've talked to a number of Infinidat customers, they're very loyal and kind of passionate. So I wonder if you could kind of put that perspective on this discussion. The impact that InfiniGuard, this announcement, that's going to have for your customers, paint a picture as to how it's going to change their business. >> Sure, so let me give you an example. One of our customers is a cloud service buyer, in North America, they focus only on healthcare. So here's a couple of key benefits that they got. First of all, they use our integration with two different backup vendors. They don't have one, they have two. So we're tightly integrated with our backup software partners. They got a 40% cost savings on CapEX, compared to the previous vendor that they had. And, they used to be able to do 30,000 backup per day, now they can do 90,000 backup a day. And by the way, that's all with the previous version of InfiniGuard, not the version we just announced on the 9th. One of our other customers, which is in AMEA and they happened to be an energy company, they were using purpose-built backup from the other vendor, and they had 14 of them, seven in data center one, and seven in data center two. With InfiniGuard, they've got one in data center one, and one in data center two. So 14 purpose-built backup appliances consolidated down into two. And on top of that, those purpose-built backup appliances from the other vendor actually had a couple recovery failures, where they were not able to recover the data. They've been installed for a year now, they've had zero recovers, zero recovery failures, whereas the previous vendor had some. And lastly, let's talk about a large global fortune financial services. So, one of the biggest in the industry, their cost savings from their previous vendor was 46%. In addition, when you look at their cyber resilience design, they were using one of those vendors that probably talks about needing two system products to do their cyber resiliency. They again were able to take those two systems out, and use one InfiniGuard solution. Again, reducing both their capital expenditure, two going to one. And then the operational expenditure, they only have to manage one InfiniGuard versus two of the other guys appliances. Those are just three examples all over the world. One in cloud service providing, one in the energy space, and one a global fortune 500 financial services company. Just some real world examples. And all those by the way, Dave, were before the enhancements of Infinisafe, and before the additional performance we've added in the launch of InfiniGuard on February 9th. >> So like I'm just kind of sketching out the business case, you know, put my CFO hat on. So you're lowering costs cause you're consolidating, so that means I need less hardware and software. But also there's probably labor costs associated with that. If I could do it faster with less resources, I got less stuff to manage. You're accelerating the backup time, so that frees up resources that I can apply elsewhere, recovery, you know, is really important. So I'm inferring faster recovery, all this lowers my risk, and then I can sort of calculate the probability of having data loss, and then what that means to my business. Am I getting that right? >> Yeah, yeah. And in fact, the other impact is on your primary service and your primary storage. If the backup window shrinks, then you're not slowing down that SAP app, that Oracle app, you know, that SQL app, whatever you're running, whether that be the financials, whether that be your logistics, whether it be your manufacturing system, every time you turn on that backup, to do that backup, that backup window slows you down. So cutting that in half has an impact on the real-world application side, which obviously most storage guys, you know, it's hard for us to quantify. But you are taking the impact of backup, and basically reducing it, if you will shrinking the backup window, so their primary applications don't get hammered as much by the backup while they're still trying to run that SAP, that Oracle or that SQL workload. >> And you're not a backup software vendor, so I have optionality there. I can pretty much choose all the popular, you know. >> Absolutely, so Veeam, Veritas, Commvault, IBM Spectrum Protect, all the majors. And in fact, one of the players I mentioned, as you were talking about the end-users, they use two different backup packages, two of 'em. So, two of the major vendors that I named, we work with them just within one account. So, we're very flexible, the user picks what they want from a backup software perspective, and we can work with anything. So, whatever they want to use, is fine with us. We integrate with all of them, we have integration, for example, also with VMware, for vVols and other aspects in container integration, so you know, whether it be our purpose-built backup appliance, InfiniGuard, or what we do with the InfiniBox, we always make sure we integrate with the surrounding environment. 'Cause storage is not an island, storage needs to exist in your data center, or your hybrid cloud data center, or what you're doing for containers. So we make sure we have integration with our InfiniBox, our InfiniBox SSA, all flash. And of course the product we're enhancing today, the InfiniGuard. >> Yeah, integration is super important in the enterprise. Enterprises want solutions, they're busy. (laughs) They don't have unlimited budget to go, you know, plugging stuff together. So, okay Eric, we got to leave it there. Thank you so much. >> Great, thank you very much Dave. Always love talking to the Cube. >> Okay, in a moment Stan Wysocki is coming in. He's the president of Mark III Systems. He's going to join us for a drill down on how InfiniGuard is impacting customers. You're watching the Cube, your global leader, in enterprise tech coverage. (gentle music)

(upbeat music) >> Okay, we just covered some of the critical aspects from Infinidat recent announcement and the importance of cyber resilience and fast recovery. Eric Hertzog is back and joining us is Stan Wysocki, who's president of Mark Three Systems. Stan, welcome to the Cube, good to see you. >> Thank you, pleasure to be here. >> Tell us about Mark Three Systems. You specialize in IT infrastructure and artificial intelligence. It says in your website. I'd love to hear more about your business. >> Yeah, yeah, definitely. You know, I think we're a little bit unique in our industry, right? There've been business partners resellers around for, we've been around for 26 years. And in 26 years, we've supported some of largest enterprise customers in the Southeast, with server storage networking virtualization. We have VCP number 94, so we've been doing that from the very beginning. But about six years ago, we realized that IT was changing, that business was changing, that the demands of the customers was changing and we needed to create the full stack message and a full-stack practice. So we hired data scientists and developers in DevOps, MLOps and gave them the environments and the tools that they could use to build experience around AI, ML deep learning. So now when we engage with our customers, not only can we handle the entire enterprise stack that they have, but we can help accelerate them on their adoption of open-source technologies, cloud native development and AI and integrating that into their business processes. >> I love it. You got to keep moving. You've been around for a long time, but you're not just sitting still. I wonder if you could comment in an Eric, I want you to comment as well. From your customer's perspective Stan, what are the big trends that you see that are impacting their business and the challenges that they're facing? >> Yeah, that's great. So kind of ties into what I just said. Today we live in a data-driven society. Everything that we do is really driven by how the customer wants to engage. And that's both an internal customer and your end user customers, on how they want to engage, how they want to consume and how they want to interact with everything out there in the world, right? So the real trends is really around engaging with the customer, but that means that you need to be data-driven, you need to adopt AI platforms, you need to adopt a more holistic view of what you're doing with your customers. That drives up the importance of the data that you have in your shop, right? So then cybersecurity becomes extremely important, not just because of the technical skills of the hacker is getting better and better, but because we're becoming more reliant on the data that we have moving forward and we're proud to partner with Infinidat in leveraging InfiniGuard and Infinni safe to really protect our customer's data. >> Great. Eric, thinking about the trends and some of the issues that Stan just mentioned, when you think about the launch and the announcement that you just made, how do you see it fitting in to Stan's business? How's how it's going to help the end customers? >> Well, I think there's one key aspect. As noted in the fortune survey of CEOs in 2021. The number one concern of CEOs of the fortune 500, was cybersecurity and they saw that as biggest threat to their business. As Stan pointed out, that becomes of the importance of the digital data, that all companies generate, of all types, financial services, healthcare, government institutions, manufacturing, you name it. So one of the key things you've got to do, is make sure that your storage estate, fits into an overall cybersecurity strategy. And with InfiniGuard, or Ifini safe technologies, we can ensure that Stan's customers and customers of our other business partners all over the world, can make sure that the data is safe, protected and can help them form a malware or ransomware attack, against that valuable data set. >> Well then you know, one of you guys could come with, I mean, we talked to CSOs and they've told us that there be could in part due to the pandemic, largely actually, their whole strategy has changed. Their spending strategies changed, no longer than just sort of putting up hardware firewalls. They're shifting their focus to two different areas, obviously endpoint, you know, cloud security is a big deal, identity access management, but ransomware, is just top of mind for everybody. And as we talked about earlier, the exposure, now the weak links, whether you're working from home, or Stan you mentioned greater sophistication of hacker. So what are you hearing from customers in this regard, Stan? >> Well, you know I think you have that, right? But then you always have, we've been doing this for 26 years. I've never heard of an IT budget that that's gone up, in any year, right? So, with the sophistication of these hackers that are coming out and the different angles that they're using to get in, it is extremely important for our customers to be very efficient and choose their security strategy and products very wisely, right? I think I read an article a year or so ago that the average enterprise had like something like 27 different security products and imagine a CSO and his team, who is struggling with their budget to manage that. So for us to be able to leverage InfiniGuard and Infini safe and to be able to provide, you know the immutable snapshots. The logical air gas, the physical air backs and offense network for recovery. That's all extremely easy to manage. I mean I talked to my customers on why they have chosen Infinidat, you know through us, right? And one of the things that they always talk about is how easy and how amazing the support is. How easy it is to install, how easy it is to manage. And normally when you have a simple product, right, you think you can sell that to an unsophisticated customers. But my most technical customers really appreciate this, because of the way Infinidat manages itself and provides the tools saying, just for example, the host tools, right? It does it in the way that they do it, so they trust it, so that they can focus on the more important tasks, rather than the tier and feeding other storage environment. >> Yeah, thank you and then when you talk to CSOs, you ask them what's the number one problem, they'll tell you lack of talent and you just nailed it. You've got on average 27 different tools, new tools coming out every day, you're getting billion dollar, VC investments and more and more companies are getting into it. It just adds to that confusion. So Stan, I wonder if you could talk about, specifically InfiniGuard, how it fits into your stack like where and how you're applying it? Maybe you could talk about some specific use cases. >> Oh yeah definitely, you know we have customers in pretty much every vertical, that we're supporting their stores environments and Infinidat plays and all of those verticals with all of our customers. One in particular a healthcare account, one of our very first Infinidat customers and over the years, is become the de facto standard, stores platform that they have. And they also now have InfiniGuard as the backup target for commovault. And this is one of those examples of the very technical discerning customer, that really demands excellence, right? So they love, you know, the three controller setup versus a dual controller set up, they love the availability and the resiliency, but then when it comes to the cybersecurity, before they moved on to this platform, they did have some ransomware attacks and they did have to pay out and it was very public. And, you know, since they've gone onto this platform, they feel much more comfortable. >> Excellent. So Eric, I want to bring you in. So let's talk through some of the options that customers have. You and I were talking earlier about, you know, the local air gap, what is that? You know, the logical air gap if you will and then the physical labor, what patterns are you seeing with customers to really try to protect themselves against some of this ransomware? How are they approaching it? >> Well, first of all, obviously, we with the InfiniGuard, has a purpose built backup appliance can work with all the various backup vendors. But because backup, is one of the first things these sophisticated ransomware, or malware it entity is going to attack. right? Otherwise the CIO will just call up say, hey, do we have a good backup? Let's recover from that. So secondary storage, AK their backup estate, is exactly the first thing they're going to target. And they do it certain viciously of course. So what are the key things we do, is we allow them to take those backup datasets, commvault for example and in Stan's example, or Vain or veritas or IBM Spectrum Protector, many other packages, even directly with databases like with Oracle Armin and allow them to create a mutable snapshots. Can't delete them, can't change them, can alter them. And then we air gap them locally, from the management framework. So in an InfiniGuard, we have a technology known as our day-to-day dupe engines ODDES. Those are really the management scanner for the entire solution. So when we create an immutable snapshots, we create a logical air gap, with ODDES, cannot alter the immutability characteristics, they cannot shorten them, they can not lengthen them, in short we take that management scheme away and create this separation. But we also allow them to replicate those backup datasets to a remote InfiniGuard box. You would set up the exact same parameters, I want to make an immutable snap every day, every 12 hours, every six hours and then you've got the duplicate. Remember the average length, from breach to closure on a cyber attack is 287 days. So once the attack starts, you don't know until they ask you for the ransom, it could be going on for 50 days, a hundred days, 150 days. And it's all done, if you will on the download, hidden. So if by the way, you happen to have a data center fire, or you happen to have a tornado or an earthquake, or some other natural disaster, you still want that data replicated to a secondary site, but then you still want the capability of the cyber resilience, as Stan pointed out. So you can do that. We can create a then a isolated fence network and we can do that on one InfiniGarden. Most of our competitors require two data protection appliances and it's public it's right on their websites. So we save you on some CapEx there and then we can do this near instantaneous recovery. And that's not just of the dataset. Some of the cyber reasons, technology you'll see out there, including on primary storage, only recovers the dataset. We can recover the entire backup data set and all the surrounding environment. So to second that Vain or Veritas, IBM spectrum protect commvault, backup is available. The backup admins or the storage admins, could immediately restored, it's ready to go. And we can do that in 15 to 30 minutes. Now that is being fast to react to a problem. >> So thank you for that. So Stan, I wonder if you could talk about the best practice Eric was just sharing, the local air gap and then the secondary, is that really in the case of a disaster, or is it also to isolate the network? What are you seeing as the gold standard that customers are applying with your advice? >> Yeah, definitely the gold standard would be three sites. We do have a lot of our customers. The one healthcare customer in particular is splits it between two sides and they are actually working with us right now to architect the third site. Just for that fact, we are down in Texas, hurricanes can come in 60, 70, 80 miles on in land. And then there's, you know, hurricane Harvey, right with all the flooding and stuff like that. So they do want to set up a third side. I think that gives them the peace of mind. And you know the whole thing about it is right. You know, having an environment like this means the CSO and his team can focus on preventing attacks, while they're very confident that their infrastructure team, can handle anything that slips by them. >> Okay, great. Thank you. We're about out of time but Eric, I wonder if you could kind of bring us home, give us a summary of, how you see InfiniGuard impacting customers, you know where's that value that business case for them. I wonder if you could just tie that note for us. >> Sure. We want to make sure that we tie everything back, normally technical value, as Stan very eloquently did with several different customers, but what we can do from a business value perspective. So as an example, one of our infiniGuard customers, is a global financial services company and they were using a solution from a different purpose-built backup appliance provider. They switched to us, not only they're able to increase the number of daily backups, from 30,000 to 90,000. So they get better data protection, but on top of that, they cut 40% of their costs. So you want to make sure that while you're doing this, you're doing things like consolidation. One of our other customers, which is in EMEA, in the European area, they had 14 purpose-built backup appliances, seven in one data center and set seven and a second data center. Now they've got two, one in one data center, one of the other, they of course do the local backups right then and there. And then they replicate, from one data center to the other data center. As both data centers are both active data centers, but differ for the other data center. So from their perspective, dramatic reduction of OPEX and CapEx, 14 physical boxes down to two. And of course the associated management of both the manpower side, but why I love to call the watch slots, power and floor. All of those things that go into an OPEX budget, they were cut dramatically, 'cause there's only two systems now, to power cool, et cetera et cetera. Floor space, Rackspace from 14. So wow, did they save money. So I think, it's not only providing that data protection and cyber resilience technology, but doing it in a cost-effective way. And as Stan pointed out, in a highly automated way, that cuts back on the manpower they need to manage these systems, because they're overworked and they need to focus on as Stan pointed out, their AI infrastructure, where they're doing for AI applications, don't have time to deal with it. So the more we automate, the better it is for them and the easier it is for everyone from the end-user perspective, as well as up in through their entire IT chain of command. >> Okay, if you want more information, you can go to infinidatguard.com or it's markiisis.com and check it out, learn about their full stack solution. A little bit about AI. Gentlemen, thanks so much for the conversation today, great to have you. >> Thank you, Dave. Now in a moment, I'm going to have some closing thoughts on the market and what we heard today. Thank you for watching the cube. You're a leader in enterprise tech coverage.

(gentle music) >> High profile cyber attacks like the SolarWinds hack, the JBS meat and the Florida municipality breach, have heightened awareness of how exposed, critical infrastructure has become. Because the pandemic has shifted employees to remote modes of work, hackers now have a much easier target to fish for credentials and exploit less secure home networks. Take the recent Log4j vulnerability, that's yet another example, of how hackers can take advantage of weak links in the chain. Now data storage companies have an important role to play in fighting cyber crime. Ultimately, they provide the equivalent of a bank vault if you will, and are responsible for storing and protecting the data that cyber criminals are targeting to steal or encrypt, in an effort to hold companies hostage, in a ransomware attack. Now in an effort to help customers understand how to protect themselves from such vulnerabilities, and how one storage company is addressing these challenges, the Cube is hosting this special presentation InfiniGuard Cyber Resilience: New Cybercrime Solutions. And we're going to speak with Eric Herzog, who's the Chief Marketing Officer of Infinidat, and then we'll bring in Stan Wysocki who is the president of Mark III Systems who is either an expert in IT infrastructure and artificial intelligence. First, let me welcome Eric Herzog back to the Cube, hello, Eric. >> Great, Dave, thank you very much, always love talking to you and the Cube, about leading edge technology solutions for end users. >> Alright let's do it. So, first we want to address the transformation and big business progress of Infinidat. New CEO, he's injected new management, new head of marketing obviously, Phil Bullinger is really been focused on accelerating the company's original vision, and doing so, Eric, in the typically unconventional style of Infinidat, you just put out a press release, capping 2021, can you set the stage for us, and give us the business update? >> Sure, so of course we summarized our 2021 results. What a very, very strong year. What a very, very strong year. We increased our bookings over 40% year to year. Even in Q4, we increased our bookings over 68%. And over 25% of the fortune 50 use an Infinidat solution, either our InfiniBox, or InfiniBox SSA, all flash array, or our Infiniguard, which is the focus of the launch we're doing today, on February 9th. >> Yeah, so I always said that Infinidat is one of the best kept secrets in the storage business. So let's talk about that hard news, what you launched on February 9th, and why it's important. >> Well, what we've done is we've got a high end enterprise purpose-built backup appliance, the InfiniGuard. We made some substantial advances in that. The key is focused on cyber resilience with what we call our infinisafe technology. Infinisafe incorporates a number of subsets, of cyber resilience from immutable snapshots, to logical air gapping, to fenced isolated networks, to almost instantaneous recovery for your backup data sets. In addition, we also dramatically improved the performance of the backup and recovery, which means, for example, if a backup window was taking three hours, now the backup window on that primary backup dataset could take only an hour and a half, which of course, as we all know backup dramatically impacts the performance of your primary applications, your primary servers, and your primary storage. So we've done both the cyber resilience aspect and then, on modern data protection, making sure that the backup and recovery are faster, for a traditional backup workload. >> So tell us a little bit more about Infinisafe, and specifically, Eric I'm interested in how it's different from other solutions, don't make me a liar, I had said, you guys always kind of take nonconventional approaches so tell us, add a little color to Infinisafe and how is it really unique from competitors? >> Sure, well Infinisafe incorporates as I mentioned, several different aspects. First of all, the immutable snapshots. So immutable snapshots can not be deleted, they cannot be altered, you cannot accelerate the rate, you can set the rate of immutable stuff, do I want to do it once a day? Do I want to do it twice a day? And obviously if a hacker could get in, you could accelerate that. Our immutable snaps are physically separated from the management schema. So the inside of an Infiniguard, we have what we call a data dedupe appliance, and that data dedupe engine, it goes ahead and it applies data reduction technology, to that back up data set. But we've divorced the immutable snapshots from the management of what we now call a DDE. So the DDE has kind of access of giving you that gap, that logical gap between the management schema of a DDE, and of course the immutable snapshot. We also combine that with this air gap technology, you've got the immutability and the air gap, which is local in that instance, but we also can do it remotely. So we can replicate from one Infiniguard in data center A, to a different Infiniguard in data center B. You then can configure that backup data set with the same immutable snapshot, and the same length, one day, half a day, six hours, whatever you choose, and then of course it'll have that same capability. The third thing we've done is very unique. We have a fenced isolated network to perform forensics. So, if the Cube has a cyber or malware attack, you need to make sure that once you've cleaned it up, off the primary storage, the primary servers, that you recover, a known good data set. So we set up this isolated fence network in which to perform that forensic analysis, to give you the appropriate good recover point. However, unlike many of our competitors, we can do it with a single InfiniBox. Some of our competitors, right on their websites say, you need two of their purpose-built backup appliances, to do cyber resilience. Meaning, twice the CapEx and twice the OpEx, which we can do with a single Infiniguard solution. And then lastly is our near instantaneous recovery. As you know, we're recovering backup data sets. We can make between 15 and 30 minutes time, the backup data set fully accessible to the backup admin or the storage admin to use their Commvault, their Veeam, their Veritas, their IBM Spectrum Protect, or whatever their backup software is, to do recovery from the InfiniGuard box, back to the primary storage using of course the backup software that they created the original dataset with. That is very unique. When you look out in the industry and look at, whether it be purpose-built backup competitors, or whether you look at primary storage competitors, almost no one talks about the speed of their recovery, and the one or two that do, talk about recovering the data set. We recover the entire environment. We are ready to go, and the backup admin, if they were, for example, Commvault, Veeam or Veritas, they could immediately start the backup, as soon as we did our recovery, which again, takes between 15 and 30 minutes, independent of the data set size. That could be 50 terabytes, it could be a petabyte, it could be two petabytes. And even two petabytes of data can be available in 15 to 30 minutes. And then of course, the backup admin can restore from that backup dataset. Very powerful and very unique in those aspects. >> Whilst the reason why this is so important is like I said, it's like the bank vault, because hackers are going to go after that backup corpus that's where the gold is, that's where all the data is. So this all really sounds good. But there's more than Infinisafe in this launch. What else should we know? >> Well, the other thing we've done is dramatically improved the performance of the purpose-built backup plants at the core. So for example, the last time we publicly announced our numbers, we were at 74 terabytes an hour, now we're 180 terabytes an hour. So of course, as we all know, when you do a backup, it impacts the performance of the primary applications, the primary servers and the primary storage. So if that backup window was taking three hours, now that we've more than doubled the performance, you could be up to 50% better. So a three hour backup window, if that's what the dataset took to be backed up, now we can get that down to an hour and a half or even faster. So that of course minimizes the impact on primary storage, primary applications, and of course your primary storage, making it much, much more efficient, from a backup perspective, and of course less impact on the primary applications, the primary servers, and primary storage. >> So I've talked to a number of Infinidat customers, they're very loyal and kind of passionate. So I wonder if you could kind of put that perspective on this discussion. The impact that InfiniGuard, this announcement, that's going to have for your customers, paint a picture as to how it's going to change their business. >> Sure, so let me give you an example. One of our customers is a cloud service buyer, in North America, they focus only on healthcare. So here's a couple of key benefits that they got. First of all, they use our integration with two different backup vendors. They don't have one, they have two. So we're tightly integrated with our backup software partners. They got a 40% cost savings on CapEX, compared to the previous vendor that they had. And, they used to be able to do 30,000 backup per day, now they can do 90,000 backup a day. And by the way, that's all with the previous version of InfiniGuard, not the version we just announced on the 9th. One of our other customers, which is in AMEA and they happened to be an energy company, they were using purpose-built backup from the other vendor, and they had 14 of them, seven in data center one, and seven in data center two. With InfiniGuard, they've got one in data center one, and one in data center two. So 14 purpose-built backup appliances consolidated down into two. And on top of that, those purpose-built backup appliances from the other vendor actually had a couple recovery failures, where they were not able to recover the data. They've been installed for a year now, they've had zero recovers, zero recovery failures, whereas the previous vendor had some. And lastly, let's talk about a large global fortune financial services. So, one of the biggest in the industry, their cost savings from their previous vendor was 46%. In addition, when you look at their cyber resilience design, they were using one of those vendors that probably talks about needing two system products to do their cyber resiliency. They again were able to take those two systems out, and use one InfiniGuard solution. Again, reducing both their capital expenditure, two going to one. And then the operational expenditure, they only have to manage one InfiniGuard versus two of the other guys appliances. Those are just three examples all over the world. One in cloud service providing, one in the energy space, and one a global fortune 500 financial services company. Just some real world examples. And all those by the way, Dave, were before the enhancements of Infinisafe, and before the additional performance we've added in the launch of InfiniGuard on February 9th. >> So like I'm just kind of sketching out the business case, you know, put my CFO hat on. So you're lowering costs cause you're consolidating, so that means I need less hardware and software. But also there's probably labor costs associated with that. If I could do it faster with less resources, I got less stuff to manage. You're accelerating the backup time, so that frees up resources that I can apply elsewhere, recovery, you know, is really important. So I'm inferring faster recovery, all this lowers my risk, and then I can sort of calculate the probability of having data loss, and then what that means to my business. Am I getting that right? >> Yeah, yeah. And in fact, the other impact is on your primary service and your primary storage. If the backup window shrinks, then you're not slowing down that SAP app, that Oracle app, you know, that SQL app, whatever you're running, whether that be the financials, whether that be your logistics, whether it be your manufacturing system, every time you turn on that backup, to do that backup, that backup window slows you down. So cutting that in half has an impact on the real-world application side, which obviously most storage guys, you know, it's hard for us to quantify. But you are taking the impact of backup, and basically reducing it, if you will shrinking the backup window, so their primary applications don't get hammered as much by the backup while they're still trying to run that SAP, that Oracle or that SQL workload. >> And you're not a backup software vendor, so I have optionality there. I can pretty much choose all the popular, you know. >> Absolutely, so Veeam, Veritas, Commvault, IBM Spectrum Protect, all the majors. And in fact, one of the players I mentioned, as you were talking about the end-users, they use two different backup packages, two of 'em. So, two of the major vendors that I named, we work with them just within one account. So, we're very flexible, the user picks what they want from a backup software perspective, and we can work with anything. So, whatever they want to use, is fine with us. We integrate with all of them, we have integration, for example, also with VMware, for vVols and other aspects in container integration, so you know, whether it be our purpose-built backup appliance, InfiniGuard, or what we do with the InfiniBox, we always make sure we integrate with the surrounding environment. 'Cause storage is not an island, storage needs to exist in your data center, or your hybrid cloud data center, or what you're doing for containers. So we make sure we have integration with our InfiniBox, our InfiniBox SSA, all flash. And of course the product we're enhancing today, the InfiniGuard. >> Yeah, integration is super important in the enterprise. Enterprises want solutions, they're busy. (laughs) They don't have unlimited budget to go, you know, plugging stuff together. So, okay Eric, we got to leave it there. Thank you so much. >> Great, thank you very much Dave. Always love talking to the Cube. >> Okay, in a moment Stan Wysocki is coming in. He's the president of Mark III Systems. He's going to join us for a drill down on how InfiniGuard is impacting customers. You're watching the Cube, your global leader, in enterprise tech coverage. (gentle music)

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by UI path. >>We'll go back to the cubes coverage of UI paths forward for big customer event. You know, this company has always bucked the trend and they're doing it again. They're having a live event, physical event. There are customers here, partners, technologists. I'm here with Lisa Martin, my co-host for the show. And we're going to talk about testing. It's a new market for UI path. If anybody knows anything about testing, it's kind of this mundane, repetitive process ripe for automation geared vice-chairs. Here's the senior vice president of testing products at UI path and Matt Elisa. Who's the product marketing lead at UI path. Gents. Welcome to the cube. Thanks for coming on. Thanks for having a feminist Likert. Explain to us how you guys think about testing both from an internal perspective and how you're going to market. >>Yeah, well, testing has been around for a long time, right? 20 twenty-five years or so when, when I came to UI pass, the first thing I looked at was like, how do our customers test RPA? And it's quite interesting. We did a survey actually with 1500 people and, uh, 27% said that they wouldn't test at all. And I thought that's really interesting. RPA is a business critical software that runs in your production environment and you probably have to test. So we came up with this idea that we create the test suite. We're using, you know, proven technology from UI pass. And, and we built this offering and brought us into market for RPA testing in for application testing. So we do both. And of course we use it internally as well. I mean, that will be, you know, eat your own dog food or drink your own champagne, I guess. So >>I want to think about it. If you, if you automate, if you, if there's an ROI to automate a process, there's gotta be an ROI to verify that it's going to work before it goes into production too. And so it's amazing that a lot of companies are not doing this and they're doing it manually, um, today. >>So, so, but so, but parts of testing have been automated, haven't they with regression testing. So can, can you guys take us through kind of the before and after and how you're approaching it versus the traditional? >>Yeah, absolutely. I mean, like I said, testing is not new, right? Um, but still when you look at the customers, they're not out to meeting more than I would say, 30, 40% of the manual tests. So still a lot of Stan manually, which I think, and we talked about this right manual testing is the, the original RPA. It's a tedious, repetitive tasks that you should not do manually. Right? And so what we are trying to bring in is now we're talking about this new role it's called the digital tester. The digital tester is an empowered. We could call a manual tester, who's able to build automation and we believe that this will truly increase the automation, even in the existing testing market. And it's going to be, I don't want to use the word game changer, but it's going change. Uh, the way testing is done. Yeah. >>And we're, we're applying, um, all the capabilities of UI path and delivering those to testers, just like we would for HR team or a, or a, a finance and accounting team. But testing even has they understand this more, they've been doing this for 20 years. They understand automation and we're going to give them things like process mining so they can figure out what tests they need to run from production data. We're going to give them task mining so they can make more human-like tests test. Exactly. Like I used to be a tester and I ran a test team. And what I used to do is I have to go out to a warehouse and I'd have to go watch people as they entered orders, to make sure I was testing it the right way. So they would like click. We usually thought they were clicking things, but they were using hotkeys. That's just an example of what they were doing. But now we can do task task mining to get that remotely, pull that data in and do tests and make more realistic tests. >>So much of the there's so much potential there. I think you were saying that only 27% are actually doing testing. So there's so much opportunity. I'm curious, where are your conversations within the customer organization? We know that automation is a board level investor topic. Where are you? Where are those discussions with the testing folks, the RPA folks, helping them come together? >>Well, that's interesting. The question, uh, we typically on the IPS, have we talked to the cos, right? The people that are professionally developing those RPAs, but very easily, we get introduced to the test side of the house. And then usually there's a joint meeting where the test people are there, the RPA people are there. And that's why we are talking about this is going to convert somehow, right? The are in different departments today. But if you think about it, five years down the road, maybe 10 years, they might be at an automation discipline for the entire enterprise. So if that answered your question about, >>Yeah. >>Going to require a cultural shift. Yeah. And we have a customer coming presenting this afternoon. and they're gonna be talking about how they, both of the teams are using a test teams and the RPA teams. And they built a reusable component library that, so when they built RPA team built their automations, they put them in a reusable library and the test team is able to recreate their test much faster reusing about 70% of the components. And so when the, when you think of automation, they're thinking about automating the application, not automating a process or a test so that people can use those like Lego blocks and build it if they're doing so, they could even, even it automation, if they wanted to start with an it automation, they could pull those components out and use those. >>I think this is game changing is quality because so often, because in this day and age of agile, it's like move fast and break things. A lot of things break. And when we heard this morning in the keynotes, how you guys are pushing code like a couple of times a week, I mean, it's just a constant. And then you do two big releases. Okay. I get, I get it for the on-prem. But when you're pushing code that fast, you don't have time to test everything. There's a lot of stuff that's unknown. And so to the extent that you can compress all those check boxes, now I can focus on the really important things that sometimes are architectural. How do you expect applying RPA to testing is going to affect the quality? Or maybe you've got some examples. Chipotle, you just mentioned, >>First of all, I mean, when you say we pushing code like bi-weekly or so, right. We're talking about continuous development. That's what it's called. Right? It's agile. You have sprint cycles, you continue to bring new code, new code, new code, and you test all the increments with it. So it's not that you building up a huge backlog for the testing on the IPA side. What I see is that there will be a transformation about the process, how they develop RPA at the moment. It's still done very much, I would say, in a waterfall way, which is agree. A big bang waterfall. Yeah. It will transition. We already have partners that apply agile methodologies to their actually RPA development. And that's going to change that. >>Okay. So it's not so it's quality for those that are in testing obviously, but, but it's, but for the waterfall guys, it's, it's compressing the time to value. Oh yeah. That's going to be the big key. That's really worth. >>I mean, what he said is Chipotle is, was able to reuse 70% of the automation components. Right. That's huge. I mean, you have to think about it. 70% can be reused from testing to RPA and vice versa. That's a huge acceleration. Also on the RPA side, you can automate more processes faster. If you have components that you can trust. >>So you were a tester. Yeah. So you were a cost center. Yes, exactly. >>Unnecessary. What's the budget. >>So could you think RPA and automation can flip that mindset? >>Yeah, totally. And that's one of the things we want to do is we want to turn testing from a cost center to a value center, give testers a new career paths, even because really testers before all you could do is you could be more technical. Maybe you become a developer or you can be a manager, but you couldn't really become like an automation architect or a senior automation person. And now we're giving them a whole different career path to go down. So it's really exciting. >>'cause I know when I came out of college, I had a job offer and I wanted to be a developer, a programmer. We called them back then. And the only job I could get was as a tester. And I was like, oh, this is miserable. I'm not doing this, but there's a, there was, there's a growth path there. They were like, Hey, do this for two or three years, maybe five years. I was like, forget it. I'm going into sales and marketing. But so what's the, what's the growth path today for the tester. And how do you see this changing? >>So you want to go, you want to, I can take that one. No, you take it. So that's a really, yeah. I mean, I did it, so really it's, I mean, we're going to be giving these guys, the testing market has been kind of not innovating for years and years and years. And so we're going to be giving these guys some new tools to make them more powerful, make even the cause. Testing is a kind of a practice that is, you know, like, like you said, you, you didn't like testing. I didn't like testing either. Actually I hate testing. So I automated it. So, um, and so that was the first thing I did. And so I think we're going to give these guys some new tools, some ways to grow their career and some ways to be even better testers, but like, like, like we've talked about process mining, test mining, like maybe they're maybe they're testing the wrong things. Maybe they're not testing, you know, maybe, you know, there, cause there's kind of this test, everything mentality we're we need to test everything and the whole release instead of like focusing in on what changed. And so I think we'll be able to help them really focus on the testing and the quality to make it more efficient as well. >>Go ahead. So do to defend the testers, right? Test is a very skilled people. Yes. They know their business, they know what to test and how to test in a way that nobody else knows that it's something we sometimes underestimate. They are not developers so that they don't write code and they don't build automations typically. But if we can equip them with tools that they can build out information, you have the brain and the muscle together, you know what I mean? You don't have to delegate the automation to some, whatever team that is maybe outsourced even you can do it. In-house and I think to some extent, that was also the story of Portland sourcing again, because they're building their own automation. Yeah. >>And it saved them time because they have deal is handoffs, you know, to an external third party to do the testing for them. And so they pulled it all in made things much more streamlined and efficient. How >>Is that? It seems like a big cultural shift within any type of organization in any industry we're using Chipola as an example here, how does your path help facilitate that cultural shift? Because that's big and we're talking about really reducing, um, or speeding time to value. >>Right. Right. And it is a lot of the agile methodologies like we're starting. So it's kind of like, we're going back in time, you know, and we're teaching these people, you know, the RPA community, all of the things that we learned from software development. Right. And so we're going to be applying that to this. And so all those agile mindset, the th the agile values, you know, those are the things that are going to help them kind of come together. And that's one of the things that Julie talked about is one of the things is they had a, kind of an agile mindset, a can-do attitude that pulled them down. >>And I think one thing that will really helps with changing the culture is empowering the people. If you give them the tools that they can do, they will do, and that will change the culture. I don't think it can come from top down. It needs to come from within and from the people. And that's what we see also with RPA, by the way, is adopted on department level and D build automations. And then at some point it becomes maybe an enterprise wide initiative, right. But somebody in HR had this idea and started >>The other thing too, is Matt, you mentioned this you'd go to a third party. So years ago in the early two thousands, we had a software company. We would use a company called agile on. They were, so I don't know if you ever heard of them. They're basically, we're a job shop. And we would throw our code over the very waterfall, throw the code over the fence. It was a black box and it was very asynchronous. And it would come back, you know, weeks later. And they say, oh, I fixed this, fixed this, but we didn't have the analytics we didn't have. There was no transparency had we had that. We would have maybe come up with new ideas or have way to improve it because we knew the product way better. And so if you can bring that, in-house now you've got much better visibility. So what, what analytics are our analytics a piece of this? And is that something? Yeah. >>Yeah. So, I mean, they'll give you an example, SAP systems, right? When you have SAP systems, customers apply transports like five or 10 a day. Every transport can change the system in a way that you might break the automation. We have the possibility to actually not only understand what's going on in this system with process mining, but we also have the possibility to do change, impact, money, and change impact. Mining tells me with every process, every transport I apply, what has changed, and we can pinpoint the test cases that you need to run. So instead of running a thousand test cases, every time we pinpoint 50 of them and you know exactly what has changed. Yeah. >>That's right. Because a lot of times you don't know what you don't know. And you're saying the machine is basically saying focus on these areas that are going to give you the biggest, that's kind of Amdahl's law. Isn't it focus on the areas that going to get the most return. Yeah. So this is a new business for UI path. You guys are targeting this as a market segment. Can you tell us more about that? >>We joined about two years ago. It takes some time to build something, right. There was a lot of proven technology there. And then we lounged, uh, I think it wasn't July last year, which was more like a private lounge. We, we didn't make much noise around it and it's gaining a lot of traction. So it's several hundred customers have already jumped on that test bandwagon, if you can call it this way. And yeah, this, this year we are pushing full speed into the testing market as well, because we see the benefits that customers get when they use both like the story from Chipotle. It has other customers like Cisco and, and more, when you hear the stories, what they were able to achieve. I mean, that's a no-brainer I think for any customer who wants to improve the automation. Yeah. >>Well, and also we're taking production grade automation and giving it to the testers and we're giving them this advanced AI so they can automate things. They weren't able to automate before, like Citrix virtual virtualized machines, point of sale systems, like 12 layer, any other business would have, they can automate all those things now that they couldn't do before, as well as everything else. And then they can also the testing tools, they talked about fragmentation this morning. That's another problem is there's a tool for mobile. There's a tool for this. There's a tool for API APIs and you have all these tools. You have to learn all these languages. We're going to give them one that they can learn and use and apply to all their technologies. And it's easy to use and it's easy to use. Yeah. >>That's kind of been the mantra of UiPath for very long time, easy to use making, making RPA simple. We've got 8,000 plus customers. You mentioned a few of them. We're going to have some of them on the program this week. How do you expect good question for you that stat that you mentioned from that survey in the very beginning of our conversation, how do you expect that needle to move in the next year? Because we're seeing so much acceleration because of the pandemic. >>A really good question, because the questions that we had in the beginning after we had the first hundred, right? The values didn't change that much. So we have now 1500 and you would assume that is pretty stable from the data. It didn't change that much. So we're still at 27% that are not testing. And that's what we see as our mission. We want to change that no customer that has more than, I dunno, five processes in production should not like not test that's crazy and we can help. And that's our mission. So, but the data is not changing. That's the interesting part. >>And I know, I know we're out of time, but, but we're how do you price this? Is it a, is it a set? Is it a subscription? Is it a usage based model? How >>It's fully included in the UI pass tool suite. So it means it's on the cloud and on-prem the pricing is the same. We are using this. There it is. Yeah. It's the same components. Like, like we're using studio for automation, we're using orchestrator, but we're using robots. We have cloud test manager on prem test manager. It's just a part of the, >>So it's a value add that you're putting into the platform. Yeah, yeah, exactly. >>Yeah. Th there are components that are priced. Yes. But I mean, it's part of the platform, how, >>But it's a module. So I paid for that module and you turn it on and then they can use it. So it's a subscription. It could be an annual term if I want multi-year term, I can do that. Exactly. Good. Great guys. Thanks so much for coming on the Cuban and good luck with this. Thank you. Great, great innovations. Okay. Keep it right there at Dave Volante for Lisa Martin, we'll be back with our coverage of UI path forward for, from the Bellagio in Las Vegas. Keep it right there.